[Robast-commits] r80 - in pkg: ROptEst ROptEst/R ROptEst/chm ROptEst/man RobAStBase RobAStBase/R RobAStBase/chm RobAStBase/man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri Mar 28 03:21:41 CET 2008
Author: ruckdeschel
Date: 2008-03-28 03:21:40 +0100 (Fri, 28 Mar 2008)
New Revision: 80
Added:
pkg/ROptEst/R/LowerCaseMultivariate.R
pkg/ROptEst/R/updateNorm.R
pkg/ROptEst/chm/getInfV.html
pkg/ROptEst/chm/updateNorm-methods.html
pkg/ROptEst/man/updateNorm-methods.Rd
pkg/RobAStBase/R/HampIC.R
pkg/RobAStBase/R/getBiasIC.R
pkg/RobAStBase/R/getRiskIC.R
pkg/RobAStBase/R/getRiskIC_UnOvShoot.R
pkg/RobAStBase/R/utils.R
pkg/RobAStBase/chm/HampIC-class.html
pkg/RobAStBase/chm/getBiasIC.html
pkg/RobAStBase/chm/getRiskIC.html
pkg/RobAStBase/chm/internals.html
pkg/RobAStBase/chm/makeIC-methods.html
pkg/RobAStBase/man/HampIC-class.Rd
pkg/RobAStBase/man/getBiasIC.Rd
pkg/RobAStBase/man/getRiskIC.Rd
pkg/RobAStBase/man/internals.Rd
pkg/RobAStBase/man/makeIC-methods.Rd
Removed:
pkg/RobAStBase/chm/makeIC.html
pkg/RobAStBase/man/makeIC.Rd
Modified:
pkg/ROptEst/NAMESPACE
pkg/ROptEst/R/AllGeneric.R
pkg/ROptEst/R/L1L2normL2deriv.R
pkg/ROptEst/R/getAsRisk.R
pkg/ROptEst/R/getInfCent.R
pkg/ROptEst/R/getInfClip.R
pkg/ROptEst/R/getInfGamma.R
pkg/ROptEst/R/getInfRobIC_asBias.R
pkg/ROptEst/R/getInfRobIC_asGRisk.R
pkg/ROptEst/R/getInfRobIC_asHampel.R
pkg/ROptEst/R/getInfStand.R
pkg/ROptEst/R/getInfV.R
pkg/ROptEst/R/getRiskIC.R
pkg/ROptEst/chm/00Index.html
pkg/ROptEst/chm/ROptEst.chm
pkg/ROptEst/chm/ROptEst.hhp
pkg/ROptEst/chm/ROptEst.toc
pkg/ROptEst/chm/getAsRisk.html
pkg/ROptEst/chm/getBiasIC.html
pkg/ROptEst/chm/getInfCent.html
pkg/ROptEst/chm/getInfClip.html
pkg/ROptEst/chm/getInfGamma.html
pkg/ROptEst/chm/getInfRobIC.html
pkg/ROptEst/chm/getInfStand.html
pkg/ROptEst/chm/getL1normL2deriv.html
pkg/ROptEst/chm/getRiskIC.html
pkg/ROptEst/chm/lowerCaseRadius.html
pkg/ROptEst/chm/minmaxBias.html
pkg/ROptEst/man/getAsRisk.Rd
pkg/ROptEst/man/getBiasIC.Rd
pkg/ROptEst/man/getInfCent.Rd
pkg/ROptEst/man/getInfClip.Rd
pkg/ROptEst/man/getInfGamma.Rd
pkg/ROptEst/man/getInfRobIC.Rd
pkg/ROptEst/man/getInfStand.Rd
pkg/ROptEst/man/getInfV.Rd
pkg/ROptEst/man/getL1normL2deriv.Rd
pkg/ROptEst/man/getRiskIC.Rd
pkg/ROptEst/man/minmaxBias.Rd
pkg/RobAStBase/NAMESPACE
pkg/RobAStBase/R/AllClass.R
pkg/RobAStBase/R/AllGeneric.R
pkg/RobAStBase/R/ContIC.R
pkg/RobAStBase/R/IC.R
pkg/RobAStBase/R/TotalVarIC.R
pkg/RobAStBase/R/Weights.R
pkg/RobAStBase/R/generateICfct.R
pkg/RobAStBase/chm/00Index.html
pkg/RobAStBase/chm/ContIC-class.html
pkg/RobAStBase/chm/ContIC.html
pkg/RobAStBase/chm/RobAStBase.chm
pkg/RobAStBase/chm/RobAStBase.hhp
pkg/RobAStBase/chm/RobAStBase.toc
pkg/RobAStBase/chm/RobWeight-class.html
pkg/RobAStBase/chm/TotalVarIC-class.html
pkg/RobAStBase/chm/getweight.html
pkg/RobAStBase/man/ContIC-class.Rd
pkg/RobAStBase/man/ContIC.Rd
pkg/RobAStBase/man/RobWeight-class.Rd
pkg/RobAStBase/man/TotalVarIC-class.Rd
pkg/RobAStBase/man/getweight.Rd
Log:
a running version... checks still have to be done;
now available: weights, biastypes, normtypes...
still to be done:
+algo for minmax-radius for
non-standard norms...
+checks for consistency with previous versions
+checks for lower case solutions...
Modified: pkg/ROptEst/NAMESPACE
===================================================================
--- pkg/ROptEst/NAMESPACE 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/NAMESPACE 2008-03-28 02:21:40 UTC (rev 80)
@@ -23,4 +23,5 @@
"lowerCaseRadius",
"minmaxBias", "getBiasIC",
"getL1normL2deriv")
-export("getL2normL2deriv")
\ No newline at end of file
+exportMethods("updateNorm")
+export("getL2normL2deriv")
Modified: pkg/ROptEst/R/AllGeneric.R
===================================================================
--- pkg/ROptEst/R/AllGeneric.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/AllGeneric.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -38,10 +38,6 @@
setGeneric("getInfV",
function(L2deriv, neighbor, biastype, ...) standardGeneric("getInfV"))
}
-if(!isGeneric("getRiskIC")){
- setGeneric("getRiskIC",
- function(IC, risk, neighbor, L2Fam, ...) standardGeneric("getRiskIC"))
-}
if(!isGeneric("optIC")){
setGeneric("optIC", function(model, risk, ...) standardGeneric("optIC"))
}
@@ -72,11 +68,6 @@
setGeneric("getL1normL2deriv",
function(L2deriv, ...) standardGeneric("getL1normL2deriv"))
}
-if(!isGeneric("getBiasIC")){
- setGeneric("getBiasIC",
- function(IC, neighbor, ...) standardGeneric("getBiasIC"))
+if(!isGeneric("updateNorm")){
+ setGeneric("updateNorm", function(normtype, ...) standardGeneric("updateNorm"))
}
-if(!isGeneric(".evalBiasIC")){
- setGeneric(".evalBiasIC",
- function(IC, neighbor, biastype, ...) standardGeneric(".evalBiasIC"))
-}
Modified: pkg/ROptEst/R/L1L2normL2deriv.R
===================================================================
--- pkg/ROptEst/R/L1L2normL2deriv.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/L1L2normL2deriv.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -7,11 +7,11 @@
})
setMethod("getL1normL2deriv", signature(L2deriv = "RealRandVariable"),
- function(L2deriv, cent, stand, Distr, ...){
+ function(L2deriv, cent, stand, Distr, normtype, ...){
integrandG <- function(x, L2, stand, cent){
X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
Y <- apply(X, 2, "%*%", t(stand))
- res <- sqrt(colSums(Y^2))
+ res <- fct(normtype)(Y)
return((res > 0)*res)
}
Added: pkg/ROptEst/R/LowerCaseMultivariate.R
===================================================================
--- pkg/ROptEst/R/LowerCaseMultivariate.R (rev 0)
+++ pkg/ROptEst/R/LowerCaseMultivariate.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,65 @@
+.LowerCaseMultivariate <- function(L2deriv, neighbor, biastype,
+ normtype, Distr, L2derivDistrSymm, trafo, z.start,
+ A.start, maxiter, tol){
+
+ w <- new("HampelWeight")
+
+
+ if(is.null(z.start)) z.start <- numeric(ncol(trafo))
+ if(is.null(A.start)) A.start <- trafo
+
+ abs.fct <- function(x, L2, stand, cent, normtype){
+ X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
+ Y <- stand %*% X
+ return(fct(normtype)(Y))
+ }
+
+ bmin.fct <- function(param, L2deriv, Distr, trafo, z.comp){
+ p <- nrow(trafo)
+ k <- ncol(trafo)
+ A <- matrix(param[1:(p*k)], ncol=k, nrow=p)
+ z <- numeric(k)
+ z[z.comp] <- param[(p*k+1):length(param)]
+
+ if (is(normtype,"SelfNorm")){
+ w0 <- w
+ cent(w0) <- z
+ stand(w0) <- A
+ weight(w0) <- minbiasweight(w0, neighbor = neighbor,
+ biastype = biastype,
+ normtype = normtype)
+ w <<- w0
+ normtype <<- updateNorm(normtype = normtype, L2 = L2deriv,
+ neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = matrix(TRUE, p,p),
+ cent = z, stand = A, w = w, ...)
+
+ }
+
+ E1 <- E(object = Distr, fun = abs.fct, L2 = L2deriv, stand = A,
+ cent = z, normtype = normtype, useApply = FALSE)
+ stA <- if (is(normtype,"QFnorm"))
+ QuadForm(normtype)%*%A else A
+
+ return(E1/sum(diag(stA %*% t(trafo))))
+ }
+
+ nrvalues <- length(L2deriv)
+ z.comp <- rep(TRUE, nrvalues)
+ for(i in 1:nrvalues)
+ if(is(L2derivDistrSymm[[i]], "SphericalSymmetry"))
+ if(L2derivDistrSymm[[i]]@SymmCenter == 0)
+ z.comp[i] <- FALSE
+
+ A.vec <- as.vector(A.start)
+ force(normtype)
+
+ erg <- optim(c(A.vec, z.start[z.comp]), bmin.fct, method = "Nelder-Mead",
+ control = list(reltol = tol, maxit = 100*maxiter),
+ L2deriv = L2deriv, Distr = Distr, trafo = trafo, z.comp = z.comp)
+
+ return(list(erg=erg, w=w, normtype = normtype))
+ }
+
+
+
Modified: pkg/ROptEst/R/getAsRisk.R
===================================================================
--- pkg/ROptEst/R/getAsRisk.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getAsRisk.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,22 +1,23 @@
###############################################################################
## asymptotic MSE
-###############################################################################
+###############################################################################
setMethod("getAsRisk", signature(risk = "asMSE",
L2deriv = "UnivariateDistribution",
- neighbor = "Neighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(),
- clip = NULL, cent = NULL, stand, trafo){
+ neighbor = "Neighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip = NULL, cent = NULL, stand, trafo){
if(!is.finite(neighbor at radius))
mse <- Inf
else
mse <- as.vector(stand)*as.vector(trafo)
return(list(asMSE = mse))
})
+
setMethod("getAsRisk", signature(risk = "asMSE",
L2deriv = "EuclRandVariable",
- neighbor = "Neighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(),
- clip = NULL, cent = NULL, stand, trafo){
+ neighbor = "Neighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip = NULL, cent = NULL, stand, trafo){
if(!is.finite(neighbor at radius))
mse <- Inf
else
@@ -29,8 +30,9 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), trafo){
+ neighbor = "ContNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, trafo){
z <- q(L2deriv)(0.5)
bias <- abs(as.vector(trafo))/E(L2deriv, function(x, z){abs(x - z)},
useApply = FALSE, z = z)
@@ -39,49 +41,26 @@
})
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), trafo){
+ neighbor = "TotalVarNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, trafo){
bias <- abs(as.vector(trafo))/(-m1df(L2deriv, 0))
return(list(asBias = bias))
})
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr,
- L2derivDistrSymm, trafo,
- z.start, A.start, maxiter, tol){
- if(is.null(z.start)) z.start <- numeric(ncol(trafo))
- if(is.null(A.start)) A.start <- trafo
-
- abs.fct <- function(x, L2, stand, cent){
- X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
- Y <- apply(X, 2, "%*%", t(stand))
-
- return(sqrt(colSums(Y^2)))
- }
- bmin.fct <- function(param, L2deriv, Distr, trafo, z.comp){
- p <- nrow(trafo)
- k <- ncol(trafo)
- A <- matrix(param[1:(p*k)], ncol=k, nrow=p)
- z <- numeric(k)
- z[z.comp] <- param[(p*k+1):length(param)]
-
- return(E(object = Distr, fun = abs.fct, L2 = L2deriv, stand = A,
- cent = z, useApply = FALSE)/sum(diag(A %*% t(trafo))))
- }
+ neighbor = "ContNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, Distr,
+ L2derivDistrSymm, trafo, z.start, A.start, maxiter, tol){
- nrvalues <- length(L2deriv)
- z.comp <- rep(TRUE, nrvalues)
- for(i in 1:nrvalues)
- if(is(L2derivDistrSymm[[i]], "SphericalSymmetry"))
- if(L2derivDistrSymm[[i]]@SymmCenter == 0)
- z.comp[i] <- FALSE
-
- A.vec <- as.vector(A.start)
- erg <- optim(c(A.vec, z.start[z.comp]), bmin.fct, method = "Nelder-Mead",
- control = list(reltol = tol, maxit = 100*maxiter),
- L2deriv = L2deriv, Distr = Distr, trafo = trafo, z.comp = z.comp)
+ normtype <- normtype(risk)
+ biastype <- biastype(risk)
+ eerg <- .LowerCaseMultivariate(L2deriv, neighbor, biastype,
+ normtype, Distr, L2derivDistrSymm, trafo, z.start,
+ A.start, maxiter, tol)
+ erg <- eerg$erg
bias <- 1/erg$value
return(list(asBias = bias))
@@ -92,38 +71,47 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
- c0 <- clip/abs(as.vector(stand))
- D1 <- L2deriv - cent/as.vector(stand)
- Cov <- (clip^2*(p(D1)(-c0) + 1 - p(D1)(c0))
- + as.vector(stand)^2*(m2df(D1, c0) - m2df(D1, -c0)))
-
- return(list(asCov = Cov))
+ neighbor = "ContNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip, cent, stand){
+# c0 <- clip/abs(as.vector(stand))
+# D1 <- L2deriv - cent/as.vector(stand)
+# Cov <- (clip^2*(p(D1)(-c0) + 1 - p(D1)(c0))
+# + as.vector(stand)^2*(m2df(D1, c0) - m2df(D1, -c0)))
+ return(list(asCov =
+ getInfV(L2deriv, neighbor, biastype(risk), clip/abs(as.vector(stand)),
+ cent/abs(as.vector(stand)), abs(as.vector(stand)))
+ ))
})
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
- g0 <- cent/abs(as.vector(stand))
- c0 <- clip/abs(as.vector(stand))
- Cov <- (abs(as.vector(stand))^2*(g0^2*p(L2deriv)(g0)
- + (g0+c0)^2*(1 - p(L2deriv)(g0+c0))
- + m2df(L2deriv, g0+c0) - m2df(L2deriv, g0)))
+ neighbor = "TotalVarNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip, cent, stand){
+# g0 <- cent/abs(as.vector(stand))
+# c0 <- clip/abs(as.vector(stand))
+# Cov <- (abs(as.vector(stand))^2*(g0^2*p(L2deriv)(g0)
+# + (g0+c0)^2*(1 - p(L2deriv)(g0+c0))
+# + m2df(L2deriv, g0+c0) - m2df(L2deriv, g0)))
+# return(list(asCov = Cov))
+ return(list(asCov =
+ getInfV(L2deriv, neighbor, biastype(risk), clip/abs(as.vector(stand)),
+ cent/abs(as.vector(stand)), abs(as.vector(stand)))
+ ))
- return(list(asCov = Cov))
})
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr, clip, cent,
- stand, norm = EuclideanNorm){
-
- return(list(asCov = .asCovMB(L2deriv, stand, cent, clip, Distr,
- norm = norm)))
+ neighbor = "ContNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, Distr, cent,
+ stand, V.comp = matrix(TRUE, ncol = nrow(stand), nrow = nrow(stand)),
+ w){
+ return(getInfV(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype(risk), Distr = Distr,
+ V.comp = V.comp, cent = cent,
+ stand = stand, w = w))
})
-
-
# Y <- as(stand %*% L2deriv - cent, "EuclRandVariable")
# absY <- sqrt(Y %*% Y)
#
@@ -140,59 +128,28 @@
# return(list(asCov = Cov))
# })
-### helping function
-.asCovMB <- function(L2, stand, cent, clip, Distr, norm){
- p <- nrow(stand)
- idx <- matrix(1:p^2,p,p)
- idx <- idx[col(idx)<=row(idx)]
- Cv <- matrix(0,p,p)
- if (clip == 0){
- Cv[idx] <- E(object = Distr, fun = function(x){
- X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
- Y <- stand %*% X
- norm0 <- norm(Y)
- ind <- 1-.eq(norm0)
- Y0 <- Y*ind/(norm0+1-ind)
- Y02 <- apply(Y0,2,function(x)x%*%t(x))[idx,]
- }, useApply = FALSE)
- }else{
- Cv[idx] <- E(object = Distr, fun = function(x){
- X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
- Y <- stand %*% X
- norm0 <- norm(Y)
- ind2 <- (norm0 < b/2)
- norm1 <- ind2*clip/2 + (1-ind2)*norm0
- ind1 <- (norm0 < b)
- ind1 + (1-ind1)*clip/norm1
- Y0 <- Y*ind1
- Y02 <- apply(Y0,2,function(x)x%*%t(x))[idx,]
- }, useApply = FALSE)
- }
- dCv <- diag(Cv)
- return(PosSemDefSymmMatrix(Cv + t(Cv) - dCv))
- }
-
-
###############################################################################
## trace of asymptotic covariance
###############################################################################
setMethod("getAsRisk", signature(risk = "trAsCov",
L2deriv = "UnivariateDistribution",
- neighbor = "UncondNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
+ neighbor = "UncondNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip, cent, stand){
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, clip = clip, cent = cent, stand = stand)$asCov
+ biastype = biastype(risk), clip = clip, cent = cent, stand = stand)$asCov
return(list(trAsCov = as.vector(Cov)))
})
setMethod("getAsRisk", signature(risk = "trAsCov",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr, clip, cent, stand){
+ neighbor = "ContNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand){
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, Distr = Distr, clip = clip,
+ biastype = biastype(risk), Distr = Distr, clip = clip,
cent = cent, stand = stand)$asCov
return(list(trAsCov = sum(diag(Cov))))
@@ -203,8 +160,9 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asUnOvShoot",
L2deriv = "UnivariateDistribution",
- neighbor = "UncondNeighborhood", biastype = "BiasType"),
- function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand, trafo){
+ neighbor = "UncondNeighborhood",
+ biastype = "ANY"),
+ function(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo){
if(identical(all.equal(neighbor at radius, 0), TRUE))
return(list(asUnOvShoot = pnorm(-risk at width/sqrt(as.vector(stand)))))
@@ -222,7 +180,8 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood", biastype = "onesidedBias"),
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"),
function(risk, L2deriv, neighbor, biastype, trafo){
D1 <- L2deriv
@@ -270,7 +229,7 @@
L2deriv = "UnivariateDistribution",
neighbor = "Neighborhood",
biastype = "onesidedBias"),
- function(risk, L2deriv, neighbor, biastype = positiveBias(),
+ function(risk, L2deriv, neighbor, biastype,
clip, cent, stand, trafo){
A <- as.vector(stand)*as.vector(trafo)
r <- neighbor at radius
Modified: pkg/ROptEst/R/getInfCent.R
===================================================================
--- pkg/ROptEst/R/getInfCent.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfCent.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -4,7 +4,7 @@
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(),
+ function(L2deriv, neighbor, biastype,
clip, cent, tol.z, symm, trafo){
if(symm) return(0)
@@ -20,7 +20,7 @@
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(),
+ function(L2deriv, neighbor, biastype,
clip, cent, tol.z, symm, trafo){
if(symm) return(-clip/2)
@@ -38,8 +38,7 @@
setMethod("getInfCent", signature(L2deriv = "RealRandVariable",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(),
- Distr, z.comp, w){
+ function(L2deriv, neighbor, biastype, Distr, z.comp, w){
integrand1 <- function(x){
weight(w)(evalRandVar(L2deriv, as.matrix(x)) [,,1])
}
@@ -67,7 +66,7 @@
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "onesidedBias"),
- function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, tol.z, symm, trafo){
if (sign(biastype)> 0){
z.fct <- function(z, c0, D1){
return(c0 - (z+c0)*p(D1)(z+c0) + m1df(D1, z+c0))
@@ -88,7 +87,7 @@
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),
- function(L2deriv, neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, tol.z, symm, trafo){
nu1 <- nu(biastype)[1]
nu2 <- nu(biastype)[2]
Modified: pkg/ROptEst/R/getInfClip.R
===================================================================
--- pkg/ROptEst/R/getInfClip.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfClip.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -5,7 +5,7 @@
L2deriv = "UnivariateDistribution",
risk = "asMSE",
neighbor = "ContNeighborhood"),
- function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ function(clip, L2deriv, risk, neighbor, biastype,
cent, symm, trafo){
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = L2deriv, risk = risk,
@@ -15,7 +15,7 @@
L2deriv = "UnivariateDistribution",
risk = "asMSE",
neighbor = "TotalVarNeighborhood"),
- function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ function(clip, L2deriv, risk, neighbor, biastype,
cent, symm, trafo){
if(symm){
return(neighbor at radius^2*clip +
@@ -31,7 +31,7 @@
L2deriv = "EuclRandVariable",
risk = "asMSE",
neighbor = "ContNeighborhood"),
- function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ function(clip, L2deriv, risk, neighbor, biastype,
Distr, stand, cent, trafo){
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = L2deriv, risk = risk, neighbor = neighbor,
@@ -46,7 +46,7 @@
L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot",
neighbor = "UncondNeighborhood"),
- function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ function(clip, L2deriv, risk, neighbor, biastype,
cent, symm, trafo){
if(symm){
return(neighbor at radius/risk at width +
Modified: pkg/ROptEst/R/getInfGamma.R
===================================================================
--- pkg/ROptEst/R/getInfGamma.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfGamma.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -5,7 +5,7 @@
risk = "asMSE",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
+ function(L2deriv, risk, neighbor, biastype, cent, clip){
c1 <- cent - clip
c2 <- cent + clip
return(m1df(L2deriv, c2) + m1df(L2deriv, c1)
@@ -19,7 +19,7 @@
risk = "asGRisk",
neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),
- function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
+ function(L2deriv, risk, neighbor, biastype, cent, clip){
return(m1df(L2deriv, cent+clip) + (cent+clip)*(1-p(L2deriv)(cent+clip)))
})
@@ -27,7 +27,7 @@
risk = "asMSE",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, risk, neighbor, biastype = symmetricBias(), Distr,
+ function(L2deriv, risk, neighbor, biastype, Distr,
stand, cent, clip){
integrandG <- function(x, L2, stand, cent, clip){
X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
@@ -48,7 +48,7 @@
risk = "asUnOvShoot",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
+ function(L2deriv, risk, neighbor, biastype, cent, clip){
return(2*(m1df(L2deriv, cent+clip) + (cent+clip)*(1-p(L2deriv)(cent+clip))))
})
@@ -59,7 +59,7 @@
risk = "asMSE",
neighbor = "ContNeighborhood",
biastype = "onesidedBias"),
- function(L2deriv, risk, neighbor, biastype = positiveBias(), cent, clip){
+ function(L2deriv, risk, neighbor, biastype, cent, clip){
c1 <- cent - clip
c2 <- cent + clip
if (sign(biastype)<0)
@@ -75,7 +75,7 @@
risk = "asMSE",
neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),
- function(L2deriv, risk, neighbor, biastype = asymmetricBias(), cent, clip){
+ function(L2deriv, risk, neighbor, biastype, cent, clip){
nu1 <- nu(biastype)[1]
nu2 <- nu(biastype)[2]
Modified: pkg/ROptEst/R/getInfRobIC_asBias.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asBias.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfRobIC_asBias.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -4,21 +4,21 @@
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asBias",
neighbor = "UncondNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo, upper, maxiter,
- tol, warn){
+ function(L2deriv, risk, neighbor, symm, trafo, maxiter,
+ tol){
minmaxBias(L2deriv, neighbor, biastype(risk), symm,
- Finfo, trafo, upper, maxiter, tol, warn)
+ trafo, maxiter, tol)
})
setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
risk = "asBias",
neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper,
- maxiter, tol, warn){
- minmaxBias(L2deriv, neighbor, biastype(risk), normtype(risk),
- Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo,
- z.start, A.start, trafo, upper,
- maxiter, tol, warn)
+ function(L2deriv, risk, neighbor, Distr, L2derivDistrSymm, z.start,
+ A.start, trafo, maxiter, tol){
+ minmaxBias(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype(risk), normtype = normtype(risk),
+ Distr = Distr, L2derivDistrSymm = L2derivDistrSymm,
+ z.start = z.start, A.start = A.start, trafo = trafo,
+ maxiter = maxiter, tol = tol)
})
@@ -26,7 +26,7 @@
neighbor = "ContNeighborhood",
biastype = "BiasType"),
function(L2deriv, neighbor, biastype = symmetricBias(), symm,
- Finfo, trafo, upper, maxiter, tol, warn){
+ trafo, maxiter, tol){
zi <- sign(as.vector(trafo))
A <- as.matrix(zi)
z <- q(L2deriv)(0.5)
@@ -60,8 +60,8 @@
neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),
function(L2deriv, neighbor, biastype = symmetricBias(),
- symm, Finfo, trafo,
- upper, maxiter, tol, warn){
+ symm, trafo,
+ maxiter, tol){
zi <- sign(as.vector(trafo))
A <- as.matrix(zi)
b <- zi*as.vector(trafo)/(-m1df(L2deriv, 0))
@@ -92,54 +92,20 @@
setMethod("minmaxBias", signature(L2deriv = "RealRandVariable",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(),
- normtype = NormType(), Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper,
- maxiter, tol, warn){
- if(is.null(z.start)) z.start <- numeric(ncol(trafo))
- if(is.null(A.start)) A.start <- trafo
+ function(L2deriv, neighbor, biastype, normtype, Distr, L2derivDistrSymm,
+ z.start, A.start, trafo, maxiter, tol){
+ eerg <- .LowerCaseMultivariate(L2deriv, neighbor, biastype,
+ normtype, Distr, L2derivDistrSymm, trafo, z.start,
+ A.start, maxiter, tol)
+ erg <- eerg$erg
-
-
- abs.fct <- function(x, L2, stand, cent, norm){
- X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
- Y <- stand %*% X
- return(fct(norm)(Y))
- }
-
- bmin.fct <- function(param, L2deriv, Distr, trafo, z.comp){
- p <- nrow(trafo)
- k <- ncol(trafo)
- A <- matrix(param[1:(p*k)], ncol=k, nrow=p)
- z <- numeric(k)
- z[z.comp] <- param[(p*k+1):length(param)]
- aL <- list(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = 0,
- Distr = Distr, norm = fct(normtype))
- normtype <<- do.call(updateNorm, aL)
- return(E(object = Distr, fun = abs.fct, L2 = L2deriv, stand = A,
- cent = z, useApply = FALSE)/sum(diag(A %*% t(trafo))))
- }
-
- nrvalues <- length(L2deriv)
- z.comp <- rep(TRUE, nrvalues)
- for(i in 1:nrvalues)
- if(is(L2derivDistrSymm[[i]], "SphericalSymmetry"))
- if(L2derivDistrSymm[[i]]@SymmCenter == 0)
- z.comp[i] <- FALSE
-
- A.vec <- as.vector(A.start)
- force(normtype)
- erg <- optim(c(A.vec, z.start[z.comp]), bmin.fct, method = "Nelder-Mead",
- control = list(reltol = tol, maxit = 100*maxiter),
- L2deriv = L2deriv, Distr = Distr, trafo = trafo, z.comp = z.comp)
b <- 1/erg$value
param <- erg$par
p <- nrow(trafo)
k <- ncol(trafo)
A <- matrix(param[1:(p*k)], ncol=k, nrow=p)
z <- numeric(k)
- z[z.comp] <- param[(p*k+1):length(param)]
+ z[erg$z.comp] <- param[(p*k+1):length(param)]
a <- as.vector(A %*% z)
d <- numeric(p)
# computation of 'd', in case 'L2derivDistr' not abs. cont.
@@ -147,13 +113,9 @@
info <- c("minimum asymptotic bias (lower case) solution")
Risk <- list(asBias = b)
- w <- new("HampelWeight")
- cent(w) <- z
- stand(w) <- A
- clip(w) <- b
- weight(w) <- minbiasweight(w, neighbor = neighbor, biastype = biastype,
- normtype = normtype)
-
+ w <- eerg$w
+ normtype <- eerg$normtype
+
return(list(A = A, a = a, b = b, d = d, risk = Risk, info = info,
w = w, biastype = biastype, normtype = normtype))
})
@@ -162,7 +124,7 @@
neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),
function(L2deriv, neighbor, biastype, symm,
- Finfo, trafo, upper, maxiter, tol, warn){
+ trafo, maxiter, tol){
nu1 <- nu(biastype)[1]
nu2 <- nu(biastype)[2]
zi <- sign(as.vector(trafo))
@@ -203,7 +165,7 @@
neighbor = "ContNeighborhood",
biastype = "onesidedBias"),
function(L2deriv, neighbor, biastype, symm,
- Finfo, trafo, upper, maxiter, tol, warn){
+ trafo, maxiter, tol){
infotxt <- c("minimum asymptotic bias (lower case) solution")
noIC <- function(){
Modified: pkg/ROptEst/R/getInfRobIC_asGRisk.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asGRisk.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfRobIC_asGRisk.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -79,7 +79,10 @@
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
biastype = biastype, clip = b, cent = a, stand = A,
trafo = trafo)
- Risk <- c(Risk, list(asBias = b))
+ Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, clip = b/A, cent = z, stand = A)
+
+ Risk <- c(Risk, list(asBias = b, asCov = Cov))
w <- new("HampelWeight")
cent(w) <- z
@@ -92,6 +95,12 @@
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info, w = w,
biastype = biastype, normtype = normtype(risk)))
})
+
+
+
+################################################################################
+
+
setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
risk = "asGRisk",
neighbor = "ContNeighborhood"),
@@ -101,6 +110,10 @@
tol, warn){
biastype <- biastype(risk)
normtype <- normtype(risk)
+
+ FI <- solve(trafo%*%solve(Finfo)%*%t(trafo))
+ if(is(normtype,"InfoNorm") || is(normtype,"SelfNorm") )
+ {QuadForm(normtype) <- PosSemDefSymmMatrix(FI); normtype(risk) <- normtype}
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
if(is.null(A.start)) A.start <- trafo %*% solve(Finfo)
@@ -112,7 +125,7 @@
res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(), neighbor = neighbor,
Distr = Distr, Finfo = Finfo, trafo = trafo)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, clip = res$b, cent = res$a,
+ biastype = biastype, cent = res$a,
stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
@@ -151,20 +164,24 @@
cent(w) <- z
stand(w) <- A
- normtype <- update(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = b,
- Distr = Distr, norm = fct(normtype))
-
+ if ((iter == 1)||is(normtype,"SelfNorm"))
+ {normtype(risk) <- normtype <- updateNorm(normtype = normtype,
+ FI = FI, L2 = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = A.comp, cent = z, stand = A, w = w)}
+
weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype,
normtype = normtype)
## new
lower0 <- getL1normL2deriv(L2deriv = L2deriv, cent = z, stand = A,
- Distr = Distr)/(1+neighbor at radius^2)
- upper0 <- sqrt( sum( diag(A%*%Finfo%*%t(A)) + (A%*%z)^2) /
+ Distr = Distr, normtype = normtype)/(1+neighbor at radius^2)
+ QF <- if(is(normtype,"QFNorm")) QuadForm(normtype) else diag(nrow(A))
+ upper0 <- sqrt( (sum( diag(QF%*%A%*%Finfo%*%t(A))) + t(A%*%z)%*%QF%*%(A%*%z)) /
((1 + neighbor at radius^2)^2-1))
if (!is.null(upper)|(iter == 1))
- {lower <- .Machine$double.eps^0.75
+ {lower <- .Machine$double.eps^0.75;
+ if(is.null(upper)) upper <- 10*upper0
}else{ lower <- lower0; upper <- upper0}
+ print(c(iter, lower,upper, lower0, upper0))
##
b <- try(uniroot(getInfClip,
## new
@@ -179,30 +196,36 @@
"=> the minimum asymptotic bias (lower case) solution is returned\n",
"If 'no' => Try again with modified starting values ",
"'z.start' and 'A.start'\n")
- res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(biastype = biastype(risk),
- normtype = normtype(risk)),
- neighbor = neighbor, Distr = Distr, DistrSymm = DistrSymm,
- L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
+ res <- getInfRobIC(L2deriv = L2deriv,
+ risk = asBias(biastype = biastype(risk),
+ normtype = normtype(risk)),
+ neighbor = neighbor, Distr = Distr, L2derivDistrSymm = L2derivDistrSymm,
z.start = z.start, A.start = A.start, trafo = trafo,
- upper = upper, maxiter = maxiter, tol = tol, warn = warn)
+ maxiter = maxiter, tol = tol)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, clip = res$b, cent = res$a, stand = res$A,
- trafo = trafo)
+ biastype = biastype, Distr = Distr,
+ cent = res$a, stand = res$A,
+ V.comp = matrix(TRUE, ncol = nrow(res$A),
+ nrow = nrow(res$A)), w = res$w)
res$risk <- c(Risk, res$risk)
return(res)
}
clip(w) <- b
- normtype <- update(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = b,
- Distr = Distr, norm = fct(normtype))
+
+ if (is(normtype,"SelfNorm"))
+ {normtype(risk) <- normtype <- updateNorm(normtype = normtype,
+ FI = FI, L2 = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = A.comp, cent = z, stand = A, w = w)}
weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype,
normtype = normtype)
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
- Distr = Distr, z.comp = z.comp, stand = A, cent = z, clip = b, w = w)
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, Distr = Distr, z.comp = z.comp,
+ w = w)
A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor,
biastype = biastype, Distr = Distr, A.comp = A.comp,
- stand = A, clip = b, cent = z, w = w, trafo = trafo)
+ cent = z, trafo = trafo, w = w)
+
prec <- max(abs(b-b.old), max(abs(A-A.old)), max(abs(z-z.old)))
cat("current precision in IC algo:\t", prec, "\n")
if(prec < tol) break
@@ -214,9 +237,10 @@
if (onesetLM){
cent(w) <- z
stand(w) <- A
- normtype <- update(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = b,
- Distr = Distr, norm = fct(normtype))
+ if (is(normtype,"SelfNorm"))
+ {normtype(risk) <- normtype <- updateNorm(normtype = normtype,
+ FI = FI, L2 = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = A.comp, cent = z, stand = A, w = w)}
weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype,
normtype = normtype)
@@ -226,7 +250,11 @@
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
biastype = biastype, clip = b, cent = a, stand = A,
trafo = trafo)
- Risk <- c(Risk, list(asBias = b))
+ Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, Distr = Distr,
+ V.comp = A.comp, cent = a,
+ stand = A, w = w)
+ Risk <- c(Risk, list(asBias = b, asCov = Cov))
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info, w = w,
biastype = biastype, normtype = normtype))
Modified: pkg/ROptEst/R/getInfRobIC_asHampel.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asHampel.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfRobIC_asHampel.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -8,6 +8,7 @@
upper, maxiter, tol, warn){
biastype <- biastype(risk)
normtype <- normtype(risk)
+
A <- trafo / E(L2deriv, function(x){x^2})
b <- risk at bound
@@ -63,7 +64,7 @@
info <- paste("optimally robust IC for 'asHampel' with bound =", round(b,3))
a <- as.vector(A)*z
Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, clip = c0, cent = z, stand = stand)
+ biastype = biastype, clip = c0, cent = z, stand = A)
# getAsRisk(risk = asHampel(), L2deriv = L2deriv, neighbor = neighbor,
# biastype = biastype, clip = b, cent = a, stand = A)$asCov
@@ -91,6 +92,10 @@
biastype <- biastype(risk)
normtype <- normtype(risk)
+ FI <- solve(trafo%*%solve(Finfo)%*%t(trafo))
+ if(is(normtype,"InfoNorm") || is(normtype,"SelfNorm") )
+ {QuadForm(normtype) <- PosSemDefSymmMatrix(FI); normtype(risk) <- normtype}
+
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
if(is.null(A.start)) A.start <- trafo
@@ -157,19 +162,19 @@
A.old <- A
cent(w) <- z
stand(w) <- A
- normtype <- update(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = b,
- Distr = Distr, norm = fct(normtype))
+ normtype(risk) <- normtype <- updateNorm(normtype = normtype, FI = FI,
+ L2 = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = A.comp, cent = z, stand = A, w = w)
weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype,
normtype = normtype)
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
- Distr = Distr, z.comp = z.comp, stand = A, cent = z, clip = b,
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, Distr = Distr, z.comp = z.comp,
w = w)
- A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
- clip = b, cent = z, A.comp = A.comp, trafo = trafo,
- Distr = Distr, stand = A, w = w)
+ A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, Distr = Distr, A.comp = A.comp,
+ cent = z, trafo = trafo, w = w)
prec <- max(max(abs(A-A.old)), max(abs(z-z.old)))
cat("current precision in IC algo:\t", prec, "\n")
if(prec < tol) break
@@ -181,9 +186,9 @@
if (onesetLM){
cent(w) <- z
stand(w) <- A
- normtype <- update(normtype = normtype, FI = Finfo,
- L2 = L2deriv, stand = A, cent = z, clip = b,
- Distr = Distr, norm = fct(normtype))
+ normtype(risk) <- normtype <- updateNorm(normtype = normtype, FI = FI,
+ L2 = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, V.comp = A.comp, cent = z, stand = A, w = w)
weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype,
normtype = normtype)
@@ -191,12 +196,14 @@
info <- paste("optimally robust IC for 'asHampel' with bound =", round(b,3))
a <- as.vector(A %*% z)
Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor,
- biastype = biastype, clip = c0, cent = z, stand = stand,
- Distr = Distr, V.comp = A.comp, w = w)
+ biastype = biastype, Distr = Distr,
+ V.comp = A.comp, cent = a,
+ stand = A, w = w)
#getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
# biastype = biastype, Distr = Distr, clip = b, cent = a,
# stand = A)$asCov
- Risk <- list(trAsCov = sum(diag(Cov)), asCov = Cov, asBias = b, asMSE = sum(diag(Cov)) + neighbor at radius^2*b^2)
+ Risk <- list(trAsCov = sum(diag(Cov)), asCov = Cov, asBias = b,
+ asMSE = sum(diag(Cov)) + neighbor at radius^2*b^2)
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info,
w = w, biastype = biastype, normtype = normtype))
Modified: pkg/ROptEst/R/getInfStand.R
===================================================================
--- pkg/ROptEst/R/getInfStand.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfStand.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -4,7 +4,7 @@
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(), clip, cent, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, trafo){
c1 <- cent - clip
c2 <- cent + clip
return(trafo/(m2df(L2deriv, c2) - m2df(L2deriv, c1)
@@ -13,7 +13,7 @@
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(), clip, cent, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, trafo){
D1 <- sign(as.vector(trafo))*L2deriv
return(trafo/(m2df(D1, cent+clip) - m2df(D1, cent) + cent*m1df(D1, cent)
- (cent+clip)*m1df(D1, cent+clip)))
@@ -21,7 +21,7 @@
setMethod("getInfStand", signature(L2deriv = "RealRandVariable",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(),
+ function(L2deriv, neighbor, biastype,
Distr, A.comp, cent, trafo, w){
w.fct <- function(x){
weight(w)(evalRandVar(L2deriv, as.matrix(x)) [,,1])
@@ -50,7 +50,7 @@
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "onesidedBias"),
- function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, trafo){
c1 <- if (sign(biastype)<0) cent - clip else -Inf
c2 <- if (sign(biastype)>0) cent + clip else Inf
m1 <- if (sign(biastype)<0) m2df(L2deriv, c1) else 0
@@ -66,7 +66,7 @@
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),
- function(L2deriv, neighbor, biastype = asymmetricBias(), clip, cent, trafo){
+ function(L2deriv, neighbor, biastype, clip, cent, trafo){
nu1 <- nu(biastype)[1]
nu2 <- nu(biastype)[2]
c1 <- cent - clip/nu1
Modified: pkg/ROptEst/R/getInfV.R
===================================================================
--- pkg/ROptEst/R/getInfV.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getInfV.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -4,7 +4,7 @@
setMethod("getInfV", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
+ function(L2deriv, neighbor, biastype, clip, cent, stand){
c1 <- cent - clip
c2 <- cent + clip
return(stand^2*(m2df(L2deriv, c2) - m2df(L2deriv, c1)
@@ -18,7 +18,7 @@
setMethod("getInfV", signature(L2deriv = "UnivariateDistribution",
neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, stand){
+ function(L2deriv, neighbor, biastype, clip, cent, stand){
c1 <- cent
c2 <- clip+clip
return(stand^2*(m2df(L2deriv, c2) - m2df(L2deriv, c1)
@@ -29,13 +29,16 @@
setMethod("getInfV", signature(L2deriv = "RealRandVariable",
neighbor = "ContNeighborhood",
biastype = "BiasType"),
- function(L2deriv, neighbor, biastype = symmetricBias(), Distr, V.comp,
- clip, cent, stand, w){
+ function(L2deriv, neighbor, biastype, Distr, V.comp,
+ cent, stand, w){
w.fct <- function(x){
(weight(w)(evalRandVar(L2deriv, as.matrix(x)) [,,1]))^2
}
+
+ cent0 <- solve(stand, cent)
+
integrandV <- function(x, L2.i, L2.j, i, j){
- return((L2.i(x) - cent[i])*(L2.j(x) - cent[j])*w.fct(x = x))
+ return((L2.i(x) - cent0[i])*(L2.j(x) - cent0[j])*w.fct(x = x))
}
nrvalues <- length(L2deriv)
@@ -58,7 +61,7 @@
setMethod("getInfV", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "onesidedBias"),
- function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, stand){
+ function(L2deriv, neighbor, biastype, clip, cent, stand){
c1 <- if (sign(biastype)<0) cent - clip else -Inf
c2 <- if (sign(biastype)>0) cent + clip else Inf
V1 <- if (sign(biastype)<0) m2df(L2deriv, c1) else 0
@@ -84,7 +87,7 @@
setMethod("getInfV", signature(L2deriv = "UnivariateDistribution",
neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),
- function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, stand){
+ function(L2deriv, neighbor, biastype, clip, cent, stand){
nu1 <- nu(biastype)[1]
nu2 <- nu(biastype)[2]
c1 <- cent - clip/nu1
Modified: pkg/ROptEst/R/getRiskIC.R
===================================================================
--- pkg/ROptEst/R/getRiskIC.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/R/getRiskIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,553 +1,36 @@
###############################################################################
## asymptotic covariance
###############################################################################
-setMethod("getRiskIC", signature(IC = "IC",
+setMethod("getRiskIC", signature(IC = "HampIC",
risk = "asCov",
neighbor = "missing",
L2Fam = "missing"),
- function(IC, risk, tol = .Machine$double.eps^0.25){
+ function(IC, risk){
L2Fam <- eval(IC at CallL2Fam)
-
- trafo <- L2Fam at param@trafo
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
-
- bias <- E(L2Fam, IC1)
- Cov <- E(L2Fam, IC1 %*% t(IC1))
-
- prec <- checkIC(IC, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asCov = list(distribution = .getDistr(L2Fam), value = Cov - bias %*% t(bias))))
+ getRiskIC(IC, risk, L2Fam)
})
-setMethod("getRiskIC", signature(IC = "IC",
+setMethod("getRiskIC", signature(IC = "HampIC",
risk = "asCov",
neighbor = "missing",
- L2Fam = "L2ParamFamily"),
- function(IC, risk, L2Fam, tol = .Machine$double.eps^0.25){
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- trafo <- L2Fam at param@trafo
- IC1 <- as(diag(dimension(IC at Curve)) %*% IC at Curve, "EuclRandVariable")
-
- bias <- E(L2Fam, IC1)
- Cov <- E(L2Fam, IC1 %*% t(IC1))
-
- prec <- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asCov = list(distribution = .getDistr(L2Fam), value = Cov - bias %*% t(bias))))
- })
-
-###############################################################################
-## trace of asymptotic covariance
-###############################################################################
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "trAsCov",
- neighbor = "missing",
L2Fam = "missing"),
- function(IC, risk, tol = .Machine$double.eps^0.25){
- trCov <- getRiskIC(IC, risk = asCov())$asCov
- trCov$value <- sum(diag(trCov$value))
-
- prec <- checkIC(IC, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(trAsCov = trCov))
+ function(IC, risk, L2Fam){
+ Cov <- IC at Risks[["asCov"]]
+ return(list(asCov = list(distribution = .getDistr(IC at L2Fam), value = Cov)))
})
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "trAsCov",
- neighbor = "missing",
- L2Fam = "L2ParamFamily"),
- function(IC, risk, L2Fam, tol = .Machine$double.eps^0.25){
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
- trCov <- getRiskIC(IC, risk = asCov(), L2Fam = L2Fam)$asCov
- trCov$value <- sum(diag(trCov$value))
- prec <- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(trAsCov = trCov))
- })
-
###############################################################################
-## asymptotic Bias
-###############################################################################
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asBias",
- neighbor = "UncondNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
- getBiasIC(IC, neighbor, biastype(risk), normtype(risk), tol)
- })
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asBias",
- neighbor = "UncondNeighborhood",
- L2Fam = "L2ParamFamily"),
- function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
- getBiasIC(IC, neighbor, L2Fam, biastype(risk), normtype(risk), tol)
- })
-###############################################################################
-## asymptotic MSE
-###############################################################################
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asMSE",
- neighbor = "UncondNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
- rad <- neighbor at radius
- if(rad == Inf) return(Inf)
-
- trCov <- getRiskIC(IC = IC, risk = trAsCov())
- Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor)
-
- nghb <- paste(neighbor at type, "with radius", neighbor at radius)
-
- prec <- checkIC(IC, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asMSE = list(distribution = .getDistr(eval(IC at CallL2Fam)),
- neighborhood = nghb,
- value = trCov$trAsCov$value + rad^2*Bias$asBias$value^2)))
- })
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asMSE",
- neighbor = "UncondNeighborhood",
- L2Fam = "L2ParamFamily"),
- function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- rad <- neighbor at radius
- if(rad == Inf) return(Inf)
-
- trCov <- getRiskIC(IC = IC, risk = trAsCov(), L2Fam = L2Fam)
- Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor, L2Fam = L2Fam,
- biastype = biastype(risk))
-
- prec <- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- nghb <- paste(neighbor at type, "with radius", neighbor at radius)
-
- return(list(asMSE = list(distribution = .getDistr(L2Fam),
- neighborhood = nghb,
- radius = neighbor at radius,
- value = trCov$trAsCov$value + rad^2*Bias$asBias$value^2)))
- })
-
-###############################################################################
-## asymptotic under-/overshoot risk
-###############################################################################
-setMethod("getRiskIC", signature(IC = "TotalVarIC",
- risk = "asUnOvShoot",
- neighbor = "UncondNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor){
- radius <- neighbor at radius
- L2Fam <- eval(IC at CallL2Fam)
- L2deriv <- L2Fam at L2derivDistr[[1]]
- if((length(L2Fam at L2derivDistr) > 1) | !is(L2deriv, "UnivariateDistribution"))
- stop("restricted to 1-dimensional parameteric models")
-
- bound <- risk at width*(-m1df(L2deriv, 0))
- if(is(neighbor, "ContNeighborhood")){
- if(radius > 2*bound)
- stop("boundedness condition is violated!")
- if(radius == 2*bound){
- zi <- sign(as.vector(trafo))
- A <- as.matrix(zi)
- b <- zi*as.vector(trafo)*2*risk at width/radius
- p0 <- p(L2deriv)(0)
- if(is(L2deriv, "AbscontDistribution"))
- ws0 <- 0
- else
- ws0 <- d(L2deriv)(0)
-
- if(zi == 1)
- a <- -b*(1-p0)/(1-ws0)
- else
- a <- b*(p0-ws0)/(1-ws0)
-
- asCov <- a^2*(p0-ws0) + (zi*a+b)^2*(1-p0)
- erg <- pnorm(-risk at width*sqrt(asCov))
- }
- }
-
- if(is(neighbor, "TotalVarNeighborhood")){
- if(radius > bound)
- stop("boundedness condition is violated!")
- if(radius == bound){
- zi <- sign(as.vector(trafo))
- A <- as.matrix(zi)
- b <- zi*as.vector(trafo)*risk at width/radius
- p0 <- p(L2deriv)(0)
- if(is(L2deriv, "AbscontDistribution"))
- ws0 <- 0
- else
- ws0 <- d(L2deriv)(0)
-
- if(zi == 1)
- a <- -b*(1-p0)/(1-ws0)
- else
- a <- b*(p0-ws0)/(1-ws0)
-
- asCov <- a^2*(p0-ws0) + (zi*a+b)^2*(1-p0)
- erg <- pnorm(-risk at width*sqrt(asCov))
- }
- }
-
- stand <- as.vector(stand(IC))
- g0 <- clipLo(IC)/abs(stand)
- c0 <- clipUp(IC)/abs(stand) - g0
- s <- sqrt(g0^2*p(L2deriv)(g0)
- + (g0+c0)^2*(1 - p(L2deriv)(g0+c0))
- + m2df(L2deriv, g0+c0) - m2df(L2deriv, g0))
- erg <- pnorm(-risk at width*s)
-
- nghb <- paste(neighbor at type, "with radius", neighbor at radius)
-
- return(list(asUnOvShoot = list(distribution = .getDistr(L2Fam),
- neighborhood = nghb, value = erg)))
- })
-###############################################################################
-## finite-sample under-/overshoot risk
-###############################################################################
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "fiUnOvShoot",
- neighbor = "ContNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left"){
- L2Fam <- eval(IC at CallL2Fam)
- Distr <- L2Fam at distribution
- if(!is(Distr, "Norm"))
- stop("restricted to 1-dimensional normal location")
-
- eps <- neighbor at radius
- tau <- risk at width
-
- if(!(is(IC, "ContIC") | is(IC, "TotalVarIC")))
- stop("'IC' has to be of class 'ContIC' or 'TotalVarIC'")
- if(is(IC, "ContIC"))
- clip <- clip(IC)/as.vector(stand(IC))
- if(is(IC, "TotalVarIC"))
- clip <- clipUp(IC)/as.vector(stand(IC))
-
- n <- sampleSize
- m <- getdistrOption("DefaultNrFFTGridPointsExponent")
-
- if(eps >= 1 - 1/(2*pnorm(risk at width))){
- warning("disjointness condition is violated!")
- erg <- 0.5
- }else{
- if(Algo == "B"){
- if(cont == "left"){
- delta1 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
- K1 <- dbinom(0:n, size = n, prob = delta1)
- P1 <- (1-eps)*pnorm(-clip-tau) + eps
- p1 <- P1/delta1
-
- summe1 <- numeric(n+1)
- summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
- summe1[n+1] <- (1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
- + pbinom(q = n/2-0.1, size = n, prob = p1)))
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
- summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
- }
- erg <- sum(summe1*K1)
- }else{
- delta2 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
- K2 <- dbinom(0:n, size = n, prob = delta2)
- P2 <- (1-eps)*pnorm(-clip+tau)
- p2 <- P2/delta2
-
- summe2 <- numeric(n+1)
- summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
- summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
- + pbinom(q = n/2-0.1, size = n, prob = p2))
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
- summe2[k+1] <- sum(P2.ste*dbinom(j, size=k, prob=p2))
- }
- erg <- sum(summe2*K2)
- }
- }else{
- M <- 2^m
- h <- 2*clip/M
- x <- seq(from = -clip, to = clip, by = h)
-
- if(cont == "right"){
- p1 <- pnorm(x+tau)
- p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
- p1[1] <- p1[1] + (1-eps)*pnorm(-clip+tau)
- p1[M] <- p1[M] + (1-eps)*pnorm(-clip-tau) + eps
- }else{
- p1 <- pnorm(x-tau)
- p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
- p1[1] <- p1[1] + (1-eps)*pnorm(-clip-tau) + eps
- p1[M] <- p1[M] + (1-eps)*pnorm(-clip+tau)
- }
-
- ## FFT
- pn <- c(p1, numeric((n-1)*M))
-
- ## convolution theorem for DFTs
- pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
- pn <- (abs(pn) >= .Machine$double.eps)*pn
- pn <- cumsum(pn)
-
- k <- n*(M-1)/2
- erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
- if(cont == "right") erg <- 1 - erg
- }
- }
-
- nghb <- paste(neighbor at type, "with radius", neighbor at radius)
-
- return(list(fiUnOvShoot = list(distribution = .getDistr(eval(IC at CallL2Fam)),
- neighborhood = nghb, value = erg)))
- })
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "fiUnOvShoot",
- neighbor = "TotalVarNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left"){
- L2Fam <- eval(IC at CallL2Fam)
- Distr <- L2Fam at distribution
- if(!is(Distr, "Norm"))
- stop("restricted to 1-dimensional normal location")
-
- delta <- neighbor at radius
- tau <- risk at width
-
- if(!(is(IC, "ContIC") | is(IC, "TotalVarIC")))
- stop("'IC' has to be of class 'ContIC' or 'TotalVarIC'")
- if(is(IC, "ContIC"))
- clip <- clip(IC)/as.vector(stand(IC))
- if(is(IC, "TotalVarIC"))
- clip <- clipUp(IC)/as.vector(stand(IC))
-
- n <- sampleSize
- m <- getdistrOption("DefaultNrFFTGridPointsExponent")
-
- if(delta >= pnorm(risk at width) - 0.5){
- warning("disjointness condition is violated!")
- erg <- 0.5
- }else{
- if(Algo == "B"){
- if(cont == "left"){
- delta1 <- min(pnorm(-clip-tau)+delta, 1) + 1 - min(pnorm(clip-tau)+delta, 1)
- K1 <- dbinom(0:n, size = n, prob = delta1)
- P1 <- min(pnorm(-clip-tau) + delta, 1)
- p1 <- min(P1/delta1, 1)
-
- summe1 <- numeric(n+1)
- summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
- summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
- }
- summe1[n+1] <- 1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
- + pbinom(q = n/2-0.1, size = n, prob = p1))
- erg <- sum(summe1*K1)
- }else{
- delta2 <- max(0, pnorm(-clip+tau)-delta) + 1 - max(0, pnorm(clip+tau)-delta)
- K2 <- dbinom(0:n, size = n, prob = delta2)
- P2 <- max(0, pnorm(-clip+tau) - delta)
- p2 <- P2/delta2
-
- summe2 <- numeric(n+1)
- summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
- summe2[k+1] <- sum(P2.ste*dbinom(j, size = k, prob = p2))
- }
- summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
- + pbinom(q = n/2-0.1, size = n, prob = p2))
- erg <- sum(summe2*K2)
- }
- }else{
- M <- 2^m
- h <- 2*clip/M
- x <- seq(from = -clip, to = clip, by = h)
-
- if(cont == "right"){
- p1 <- pnorm(x+tau)
- p1 <- p1[2:(M + 1)] - p1[1:M]
- p1[1] <- p1[1] + pnorm(-clip+tau) - delta
- p1[M] <- p1[M] + pnorm(-clip-tau) + delta
- }else{
- p1 <- pnorm(x-tau)
- p1 <- p1[2:(M + 1)] - p1[1:M]
- p1[1] <- p1[1] + pnorm(-clip-tau) + delta
- p1[M] <- p1[M] + pnorm(-clip+tau) - delta
- }
-
- ## FFT
- pn <- c(p1, numeric((n-1)*M))
-
- ## convolution theorem for DFTs
- pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
- pn <- (abs(pn) >= .Machine$double.eps)*pn
- pn <- cumsum(pn)
-
- k <- n*(M-1)/2
- erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
- if(cont == "right") erg <- 1-erg
- }
- }
-
- nghb <- paste(neighbor at type, "with radius", neighbor at radius)
-
- return(list(fiUnOvShoot = list(distribution = .getDistr(eval(IC at CallL2Fam)),
- neighborhood = nghb, value = erg)))
- })
-
-
-###############################################################################
## asymptotic Bias for various types
###############################################################################
-setMethod("getBiasIC", signature(IC = "IC",
+setMethod("getBiasIC", signature(IC = "HampIC",
neighbor = "UncondNeighborhood"),
- function(IC, neighbor, L2Fam, biastype = symmetricBias(),
- normtype = NormType(), tol = .Machine$double.eps^0.25){
+ function(IC, neighbor, L2Fam){
if(missing(L2Fam))
{misF <- TRUE; L2Fam <- eval(IC at CallL2Fam)}
- D1 <- L2Fam at distribution
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(D1)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- x <- as.matrix(r(D1)(1e5))
- x <- as.matrix(x[!duplicated(x),])
- Bias <- .evalBiasIC(IC = IC, neighbor = neighbor, biastype = biastype,
- normtype = normtype, x = x, trafo = L2Fam at param@trafo)
-
- prec <- if(misF) checkIC(IC, out = FALSE) else
- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
return(list(asBias = list(distribution = .getDistr(L2Fam),
- neighborhood = neighbor at type, value = Bias)))
+ neighborhood = neighbor at type, value = IC at Risks[["asBias"]])))
})
-setMethod("getBiasIC", signature(IC = "ContIC",
- neighbor = "UncondNeighborhood"),
- function(IC, neighbor, L2Fam, biastype = symmetricBias(),
- normtype = NormType(), tol = .Machine$double.eps^0.25){
- if(missing(L2Fam))
- {misF <- TRUE; L2Fam <- eval(IC at CallL2Fam)}
- D1 <- L2Fam at distribution
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(D1)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- x <- as.matrix(r(D1)(1e5))
- x <- as.matrix(x[!duplicated(x),])
- Bias <- .evalBiasIC(IC = IC, neighbor = neighbor, biastype = biastype,
- normtype = normtype, x = x, trafo = L2Fam at param@trafo)
-
-
- prec <- if(misF) checkIC(IC, out = FALSE) else
- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asBias = list(distribution = .getDistr(L2Fam),
- neighborhood = neighbor at type, value = Bias)))
- })
-
-setMethod(".evalBiasIC", signature(IC = "IC",
- neighbor = "ContNeighborhood",
- biastype = "BiasType"),
- function(IC, neighbor, biastype, normtype, x, trafo){
- ICx <- evalRandVar(as(diag(dimension(IC at Curve)) %*% IC at Curve,
- "EuclRandVariable"),x)
-
- return(max(fct(normtype)(ICx)))}
- )
-
-setMethod(".evalBiasIC", signature(IC = "IC",
- neighbor = "TotalVarNeighborhood",
- biastype = "BiasType"),
- function(IC, neighbor, biastype, normtype, x, trafo){
- if(nrow(trafo) > 1)
- stop("not yet implemented for dimension > 1")
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
- res <- evalRandVar(IC1, x)
- return(max(res) - min(res))}
- )
-
-setMethod(".evalBiasIC", signature(IC = "IC",
- neighbor = "ContNeighborhood",
- biastype = "onesidedBias"),
- function(IC, neighbor, biastype, x, trafo){
- if(nrow(trafo) > 1)
- stop("not yet implemented for dimension > 1")
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
- res <- evalRandVar(IC1, x)
- if (sign(biastype)>0)
- return(max(res))
- else return(-min(res))
- })
-
-setMethod(".evalBiasIC", signature(IC = "IC",
- neighbor = "ContNeighborhood",
- biastype = "asymmetricBias"),
- function(IC, neighbor, biastype, x, trafo){
- if(nrow(trafo) > 1)
- stop("not yet implemented for dimension > 1")
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
- res <- evalRandVar(IC1, x)
- return(max(res)/nu(biastype)[2] -
- min(res)/nu(biastype)[1])}
- )
-
-.getDistr <- function(L2Fam){
- slots <- slotNames(L2Fam at distribution@param)
- slots <- slots[slots != "name"]
- nrvalues <- length(slots)
- if (nrvalues > 0) {
- values = numeric(nrvalues)
- for (i in 1:nrvalues)
- values[i] <- attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
-
- paramstring <- paste("(", paste(values, collapse = ", "), ")", sep = "")
- }
- distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
-}
\ No newline at end of file
Added: pkg/ROptEst/R/updateNorm.R
===================================================================
--- pkg/ROptEst/R/updateNorm.R (rev 0)
+++ pkg/ROptEst/R/updateNorm.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,11 @@
+setMethod("updateNorm", "NormType", function(normtype, ...) normtype)
+setMethod("updateNorm", "InfoNorm", function(normtype, FI, ...)
+ {QuadForm(normtype) <- PosSemDefSymmMatrix(FI); normtype})
+setMethod("updateNorm", "SelfNorm", function(normtype, L2, neighbor, biastype,
+ Distr, V.comp, cent, stand, w, ...)
+ {Cv <- getInfV(L2deriv = L2, neighbor = neighbor,
+ biastype = biastype, Distr = Distr,
+ V.comp = V.comp, cent = cent, stand = stand, w = w)
+ QuadForm(normtype) <- PosSemDefSymmMatrix(solve(Cv)); normtype})
+
+
\ No newline at end of file
Modified: pkg/ROptEst/chm/00Index.html
===================================================================
--- pkg/ROptEst/chm/00Index.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/00Index.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -18,6 +18,7 @@
<a href="#M">M</a>
<a href="#O">O</a>
<a href="#R">R</a>
+<a href="#U">U</a>
</p>
<table width="100%">
</table>
@@ -27,39 +28,39 @@
<table width="100%">
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,RealRandVariable,ContNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,ANY-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
-<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,RealRandVariable,ContNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,EuclRandVariable,Neighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,UnivariateDistribution,Neighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,ANY-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk-methods</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getBiasIC.html">getBiasIC</a></td>
<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
-<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,UncondNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,HampIC,UncondNeighborhood-method</a></td>
<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
<tr><td width="25%"><a href="getBiasIC.html">getBiasIC-methods</a></td>
<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
@@ -173,6 +174,20 @@
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
<tr><td width="25%"><a href="getInfStand.html">getInfStand-methods</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
+<tr><td width="25%"><a href="getInfV.html">getInfV-methods</a></td>
+<td>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</td></tr>
<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv</a></td>
<td>Calculation of L1 norm of L2derivative</td></tr>
<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv,RealRandVariable-method</a></td>
@@ -185,28 +200,10 @@
<td>Calculation of L2 norm of L2derivative</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method</a></td>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,HampIC,asCov,missing,L2ParamFamily-method</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,missing-method</a></td>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,HampIC,asCov,missing,missing-method</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,L2ParamFamily-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,L2ParamFamily-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC-methods</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
</table>
@@ -230,6 +227,8 @@
<td>Computation of the lower case radius</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,ANY-method</a></td>
<td>Computation of the lower case radius</td></tr>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,UnivariateDistribution,ContNeighborhood,asMSE,onesidedBias-method</a></td>
+<td>Computation of the lower case radius</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius-methods</a></td>
<td>Computation of the lower case radius</td></tr>
</table>
@@ -245,6 +244,8 @@
<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="minmaxBias.html">minmaxBias-methods</a></td>
@@ -286,4 +287,19 @@
<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC-methods</a></td>
<td>Generic function for the computation of the radius minimax IC</td></tr>
</table>
+
+<h2><a name="U">-- U --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="updateNorm-methods.html">updateNorm</a></td>
+<td>Methods for Function updateNorm in Package ‘ROptEst’ </td></tr>
+<tr><td width="25%"><a href="updateNorm-methods.html">updateNorm,InfoNorm-method</a></td>
+<td>Methods for Function updateNorm in Package ‘ROptEst’ </td></tr>
+<tr><td width="25%"><a href="updateNorm-methods.html">updateNorm,NormType-method</a></td>
+<td>Methods for Function updateNorm in Package ‘ROptEst’ </td></tr>
+<tr><td width="25%"><a href="updateNorm-methods.html">updateNorm,SelfNorm-method</a></td>
+<td>Methods for Function updateNorm in Package ‘ROptEst’ </td></tr>
+<tr><td width="25%"><a href="updateNorm-methods.html">updateNorm-methods</a></td>
+<td>Methods for Function updateNorm in Package ‘ROptEst’ </td></tr>
+</table>
</body></html>
Modified: pkg/ROptEst/chm/ROptEst.chm
===================================================================
(Binary files differ)
Modified: pkg/ROptEst/chm/ROptEst.hhp
===================================================================
--- pkg/ROptEst/chm/ROptEst.hhp 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/ROptEst.hhp 2008-03-28 02:21:40 UTC (rev 80)
@@ -23,6 +23,7 @@
getInfGamma.html
getInfRobIC.html
getInfStand.html
+getInfV.html
getL1normL2deriv.html
getL2normL2deriv.html
getRiskIC.html
@@ -32,3 +33,4 @@
optIC.html
optRisk.html
radiusMinimaxIC.html
+updateNorm-methods.html
Modified: pkg/ROptEst/chm/ROptEst.toc
===================================================================
--- pkg/ROptEst/chm/ROptEst.toc 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/ROptEst.toc 2008-03-28 02:21:40 UTC (rev 80)
@@ -14,15 +14,15 @@
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asBias,RealRandVariable,ContNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
+<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
@@ -30,27 +30,27 @@
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asCov,RealRandVariable,ContNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asMSE,EuclRandVariable,Neighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asMSE,UnivariateDistribution,Neighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
@@ -58,15 +58,15 @@
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method">
+<param name="Name" value="getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,ANY-method">
<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
@@ -78,7 +78,7 @@
<param name="Local" value="getBiasIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getBiasIC,IC,UncondNeighborhood-method">
+<param name="Name" value="getBiasIC,HampIC,UncondNeighborhood-method">
<param name="Local" value="getBiasIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
@@ -306,74 +306,66 @@
<param name="Local" value="getInfStand.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getL1normL2deriv">
-<param name="Local" value="getL1normL2deriv.html">
+<param name="Name" value="getInfV">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getL1normL2deriv,RealRandVariable-method">
-<param name="Local" value="getL1normL2deriv.html">
+<param name="Name" value="getInfV,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getL1normL2deriv,UnivariateDistribution-method">
-<param name="Local" value="getL1normL2deriv.html">
+<param name="Name" value="getInfV,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getL1normL2deriv-methods">
-<param name="Local" value="getL1normL2deriv.html">
+<param name="Name" value="getInfV,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getL2normL2deriv">
-<param name="Local" value="getL2normL2deriv.html">
+<param name="Name" value="getInfV,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getInfV,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getInfV-methods">
+<param name="Local" value="getInfV.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asBias,UncondNeighborhood,missing-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getL1normL2deriv">
+<param name="Local" value="getL1normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asCov,missing,L2ParamFamily-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getL1normL2deriv,RealRandVariable-method">
+<param name="Local" value="getL1normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asCov,missing,missing-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getL1normL2deriv,UnivariateDistribution-method">
+<param name="Local" value="getL1normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getL1normL2deriv-methods">
+<param name="Local" value="getL1normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,asMSE,UncondNeighborhood,missing-method">
-<param name="Local" value="getRiskIC.html">
+<param name="Name" value="getL2normL2deriv">
+<param name="Local" value="getL2normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method">
+<param name="Name" value="getRiskIC">
<param name="Local" value="getRiskIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method">
+<param name="Name" value="getRiskIC,HampIC,asCov,missing,L2ParamFamily-method">
<param name="Local" value="getRiskIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,trAsCov,missing,L2ParamFamily-method">
+<param name="Name" value="getRiskIC,HampIC,asCov,missing,missing-method">
<param name="Local" value="getRiskIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,IC,trAsCov,missing,missing-method">
-<param name="Local" value="getRiskIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method">
-<param name="Local" value="getRiskIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="getRiskIC-methods">
<param name="Local" value="getRiskIC.html">
</OBJECT>
@@ -410,6 +402,10 @@
<param name="Local" value="lowerCaseRadius.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCaseRadius,UnivariateDistribution,ContNeighborhood,asMSE,onesidedBias-method">
+<param name="Local" value="lowerCaseRadius.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="lowerCaseRadius-methods">
<param name="Local" value="lowerCaseRadius.html">
</OBJECT>
@@ -430,6 +426,10 @@
<param name="Local" value="minmaxBias.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="minmaxBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
+<param name="Local" value="minmaxBias.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
<param name="Local" value="minmaxBias.html">
</OBJECT>
@@ -489,6 +489,26 @@
<param name="Name" value="radiusMinimaxIC-methods">
<param name="Local" value="radiusMinimaxIC.html">
</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="updateNorm">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="updateNorm,InfoNorm-method">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="updateNorm,NormType-method">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="updateNorm,SelfNorm-method">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="updateNorm-methods">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
</UL>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Package ROptEst: Titles">
@@ -543,6 +563,10 @@
<param name="Local" value="getBiasIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic Function for the Computation of the asymptotic Variance of a Hampel type IC">
+<param name="Local" value="getInfV.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of the minimal risk">
<param name="Local" value="optRisk.html">
</OBJECT>
@@ -562,6 +586,10 @@
<param name="Name" value="Generic Function for the Computation of the Standardizing Matrix ">
<param name="Local" value="getInfStand.html">
</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Methods for Function updateNorm in Package `ROptEst' ">
+<param name="Local" value="updateNorm-methods.html">
+</OBJECT>
</UL>
</UL>
</BODY></HTML>
Modified: pkg/ROptEst/chm/getAsRisk.html
===================================================================
--- pkg/ROptEst/chm/getAsRisk.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getAsRisk.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -7,19 +7,19 @@
<table width="100%"><tr><td>getAsRisk(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getAsRisk">
<param name="keyword" value="R: getAsRisk-methods">
-<param name="keyword" value="R: getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asMSE,UnivariateDistribution,Neighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asMSE,EuclRandVariable,Neighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,ANY-method">
<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
-<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method">
-<param name="keyword" value="R: getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asBias,RealRandVariable,ContNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asCov,RealRandVariable,ContNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,ANY-method">
+<param name="keyword" value="R: getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY-method">
<param name="keyword" value="R: getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method">
<param name="keyword" value=" Generic Function for Computation of Asymptotic Risks">
</object>
@@ -43,15 +43,15 @@
getAsRisk(risk, L2deriv, neighbor, biastype, ...)
## S4 method for signature 'asMSE, UnivariateDistribution,
-## Neighborhood, BiasType':
+## Neighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
## S4 method for signature 'asMSE, EuclRandVariable,
-## Neighborhood, BiasType':
-getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+## Neighborhood, ANY':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo, norm = EuclideanNorm)
## S4 method for signature 'asBias, UnivariateDistribution,
-## ContNeighborhood, BiasType':
+## ContNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
## S4 method for signature 'asBias, UnivariateDistribution,
@@ -63,36 +63,36 @@
getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
## S4 method for signature 'asBias, UnivariateDistribution,
-## TotalVarNeighborhood, BiasType':
+## TotalVarNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
## S4 method for signature 'asBias, RealRandVariable,
-## ContNeighborhood, BiasType':
+## ContNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
- z.start, A.start, maxiter, tol)
+ z.start, A.start, maxiter, tol, norm = EuclideanNorm)
## S4 method for signature 'asCov, UnivariateDistribution,
-## ContNeighborhood, BiasType':
+## ContNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'asCov, UnivariateDistribution,
-## TotalVarNeighborhood, BiasType':
+## TotalVarNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'asCov, RealRandVariable,
-## ContNeighborhood, BiasType':
-getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+## ContNeighborhood, ANY':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
## S4 method for signature 'trAsCov,
-## UnivariateDistribution, UncondNeighborhood, BiasType':
+## UnivariateDistribution, UncondNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'trAsCov, RealRandVariable,
-## ContNeighborhood, BiasType':
-getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+## ContNeighborhood, ANY':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
## S4 method for signature 'asUnOvShoot,
-## UnivariateDistribution, UncondNeighborhood, BiasType':
+## UnivariateDistribution, UncondNeighborhood, ANY':
getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
## S4 method for signature 'asSemivar,
@@ -117,7 +117,7 @@
object of class <code>"Neighborhood"</code>. </td></tr>
<tr valign="top"><td><code>biastype</code></td>
<td>
-object of class <code>"BiasType"</code>. </td></tr>
+object of class <code>"ANY"</code>. </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
@@ -151,6 +151,9 @@
<tr valign="top"><td><code>tol</code></td>
<td>
the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>norm</code></td>
+<td>
+function; norm for the parameter space</td></tr>
</table>
<h3>Value</h3>
@@ -161,15 +164,15 @@
<h3>Methods</h3>
<dl>
-<dt>risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
+<dt>risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "ANY":</dt><dd>computes asymptotic mean square error in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
+<dt>risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "ANY":</dt><dd>computes asymptotic mean square error in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "ANY":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
@@ -178,30 +181,30 @@
<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "ANY":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "ANY":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "ANY":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods
+<dt>risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "ANY":</dt><dd>computes trace of asymptotic covariance in methods
for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods for
+<dt>risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":</dt><dd>computes trace of asymptotic covariance in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic under-/overshoot risk in methods for
+<dt>risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "ANY":</dt><dd>computes asymptotic under-/overshoot risk in methods for
function <code>getInfRobIC</code>. </dd>
Modified: pkg/ROptEst/chm/getBiasIC.html
===================================================================
--- pkg/ROptEst/chm/getBiasIC.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getBiasIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -7,7 +7,7 @@
<table width="100%"><tr><td>getBiasIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getBiasIC">
<param name="keyword" value="R: getBiasIC-methods">
-<param name="keyword" value="R: getBiasIC,IC,UncondNeighborhood-method">
+<param name="keyword" value="R: getBiasIC,HampIC,UncondNeighborhood-method">
<param name="keyword" value=" Generic function for the computation of the asymptotic bias for an IC">
</object>
@@ -27,11 +27,8 @@
<pre>
getBiasIC(IC, neighbor, ...)
-## S4 method for signature 'IC, UncondNeighborhood':
-getBiasIC(IC, neighbor, L2Fam,
- biastype = symmetricBias(),
- tol = .Machine$double.eps^0.25)
-
+## S4 method for signature 'HampIC, UncondNeighborhood':
+getBiasIC(IC, neighbor, L2Fam)
</pre>
@@ -44,42 +41,28 @@
<tr valign="top"><td><code>neighbor</code></td>
<td>
object of class <code>"Neighborhood"</code>. </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
<tr valign="top"><td><code>L2Fam</code></td>
<td>
-object of class <code>"L2ParamFamily"</code> or missing. </td></tr>
-<tr valign="top"><td><code>biastype</code></td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
<td>
-object of class <code>"BiasType"</code>. </td></tr>
-<tr valign="top"><td><code>tol</code></td>
-<td>
-the desired accuracy (convergence tolerance).</td></tr>
+additional parameters </td></tr>
</table>
<h3>Details</h3>
-<p>
-To make sure that the results are valid, it is recommended
-to include an additional check of the IC properties of <code>IC</code>
-using <code>checkIC</code>.
-</p>
+
<h3>Value</h3>
<p>
-The asymptotic bias of an IC is computed.</p>
+The bias of the IC is computed.</p>
<h3>Methods</h3>
<dl>
-</p>
-
-<dt>IC = "IC", neighbor = "UncondNeighborhood":</dt><dd>asymptotic bias of <code>IC</code> in case of unconditional neighborhoods. </dd>
-
-<p>
+<dt>IC = "HampIC", neighbor = "UncondNeighborhood"</dt><dd>reads off the as. bias from the risks-slot of the IC. </dd>
</dl>
<h3>Note</h3>
@@ -92,7 +75,6 @@
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -100,15 +82,22 @@
<h3>References</h3>
<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Bias
+of M-estimators on Neighborhoods.
</p>
Modified: pkg/ROptEst/chm/getInfCent.html
===================================================================
--- pkg/ROptEst/chm/getInfCent.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getInfCent.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -38,27 +38,27 @@
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, BiasType':
getInfCent(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
## S4 method for signature 'UnivariateDistribution,
## TotalVarNeighborhood, BiasType':
getInfCent(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
## S4 method for signature 'RealRandVariable,
## ContNeighborhood, BiasType':
getInfCent(L2deriv,
- neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+ neighbor, biastype, z.comp, stand, cent, clip, w)
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, onesidedBias':
getInfCent(L2deriv,
- neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, asymmetricBias':
getInfCent(L2deriv,
- neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
</pre>
@@ -100,6 +100,9 @@
<td>
logical vector: indication which components of the
centering constant have to be computed. </td></tr>
+<tr valign="top"><td><code>w</code></td>
+<td>
+object of class <code>RobWeight</code>; current weight</td></tr>
</table>
<h3>Value</h3>
Modified: pkg/ROptEst/chm/getInfClip.html
===================================================================
--- pkg/ROptEst/chm/getInfClip.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getInfClip.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -52,7 +52,7 @@
## S4 method for signature 'numeric,
## UnivariateDistribution, asSemivar, ContNeighborhood':
-getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)
</pre>
Modified: pkg/ROptEst/chm/getInfGamma.html
===================================================================
--- pkg/ROptEst/chm/getInfGamma.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getInfGamma.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -37,32 +37,32 @@
## S4 method for signature 'UnivariateDistribution, asMSE,
## ContNeighborhood, BiasType':
getInfGamma(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
## S4 method for signature 'UnivariateDistribution,
## asGRisk, TotalVarNeighborhood, BiasType':
getInfGamma(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
## S4 method for signature 'RealRandVariable, asMSE,
## ContNeighborhood, BiasType':
getInfGamma(L2deriv,
- risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
+ risk, neighbor, biastype, Distr, stand, cent, clip)
## S4 method for signature 'UnivariateDistribution,
## asUnOvShoot, ContNeighborhood, BiasType':
getInfGamma(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
## S4 method for signature 'UnivariateDistribution, asMSE,
## ContNeighborhood, onesidedBias':
getInfGamma(L2deriv,
- risk, neighbor, biastype = positiveBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
## S4 method for signature 'UnivariateDistribution, asMSE,
## ContNeighborhood, asymmetricBias':
getInfGamma(L2deriv,
- risk, neighbor, biastype = asymmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
</pre>
Modified: pkg/ROptEst/chm/getInfRobIC.html
===================================================================
--- pkg/ROptEst/chm/getInfRobIC.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getInfRobIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -52,13 +52,13 @@
## S4 method for signature 'UnivariateDistribution, asBias,
## UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+getInfRobIC(L2deriv, risk, neighbor, symm, trafo,
+ maxiter, tol)
## S4 method for signature 'RealRandVariable, asBias,
## ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+getInfRobIC(L2deriv, risk, neighbor, Distr,
+ L2derivDistrSymm, z.start, A.start, trafo, maxiter, tol)
## S4 method for signature 'UnivariateDistribution,
## asHampel, UncondNeighborhood':
Modified: pkg/ROptEst/chm/getInfStand.html
===================================================================
--- pkg/ROptEst/chm/getInfStand.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getInfStand.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -36,27 +36,27 @@
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, BiasType':
getInfStand(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'UnivariateDistribution,
## TotalVarNeighborhood, BiasType':
getInfStand(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'RealRandVariable,
## ContNeighborhood, BiasType':
getInfStand(L2deriv,
- neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+ neighbor, biastype, Distr, A.comp, stand, clip, cent, trafo, w)
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, BiasType':
getInfStand(L2deriv,
- neighbor, biastype = positiveBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, BiasType':
getInfStand(L2deriv,
- neighbor, biastype = asymmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
</pre>
@@ -95,6 +95,9 @@
<td>
matrix: indication which components of the standardizing
matrix have to be computed. </td></tr>
+<tr valign="top"><td><code>w</code></td>
+<td>
+object of class <code>RobWeight</code>; current weight</td></tr>
</table>
<h3>Value</h3>
Added: pkg/ROptEst/chm/getInfV.html
===================================================================
--- pkg/ROptEst/chm/getInfV.html (rev 0)
+++ pkg/ROptEst/chm/getInfV.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,145 @@
+<html><head><title>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getInfV(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getInfV">
+<param name="keyword" value="R: getInfV-methods">
+<param name="keyword" value="R: getInfV,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfV,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfV,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfV,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
+<param name="keyword" value="R: getInfV,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
+<param name="keyword" value=" Generic Function for the Computation of the asymptotic Variance of a Hampel type IC">
+</object>
+
+
+<h2>Generic Function for the Computation of the asymptotic Variance of a Hampel type IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal clipping bound
+in case of infinitesimal robust models. This function is rarely called
+directly. It is used to compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfV(L2deriv, neighbor, biastype, ...)
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfV(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getInfV(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfV(L2deriv,
+ neighbor, biastype, Distr, V.comp, cent, stand,
+ w)
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, onesidedBias':
+getInfV(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+getInfV(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+positive real: clipping bound </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>V.comp</code></td>
+<td>
+matrix: indication which components of the standardizing
+matrix have to be computed. </td></tr>
+<tr valign="top"><td><code>w</code></td>
+<td>
+object of class <code>RobWeight</code>; current weight</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The asymptotic variance of an ALE to IC of Hampel type is computed.</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/ROptEst/chm/getL1normL2deriv.html
===================================================================
--- pkg/ROptEst/chm/getL1normL2deriv.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getL1normL2deriv.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -32,7 +32,7 @@
## S4 method for signature 'UnivariateDistribution':
getL1normL2deriv(L2deriv,
- cent, stand, Distr, ...)
+ cent, stand, Distr, normtype, ...)
</pre>
@@ -52,6 +52,9 @@
<tr valign="top"><td><code>Distr</code></td>
<td>
distribution of the L2derivative</td></tr>
+<tr valign="top"><td><code>normtype</code></td>
+<td>
+object of class <code>NormType</code>; the norm under which we work</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
further arguments (not used at the moment)</td></tr>
Modified: pkg/ROptEst/chm/getRiskIC.html
===================================================================
--- pkg/ROptEst/chm/getRiskIC.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/getRiskIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -7,17 +7,8 @@
<table width="100%"><tr><td>getRiskIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getRiskIC">
<param name="keyword" value="R: getRiskIC-methods">
-<param name="keyword" value="R: getRiskIC,IC,asCov,missing,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,asCov,missing,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,HampIC,asCov,missing,missing-method">
+<param name="keyword" value="R: getRiskIC,HampIC,asCov,missing,L2ParamFamily-method">
<param name="keyword" value=" Generic function for the computation of a risk for an IC">
</object>
@@ -37,47 +28,14 @@
<pre>
getRiskIC(IC, risk, neighbor, L2Fam, ...)
-## S4 method for signature 'IC, asCov, missing, missing':
-getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, asCov, missing,
-## L2ParamFamily':
-getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, trAsCov, missing, missing':
-getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, trAsCov, missing,
-## L2ParamFamily':
-getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## S4 method for signature 'HampIC, asCov, missing,
## missing':
-getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk)
-## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## S4 method for signature 'HampIC, asCov, missing,
## L2ParamFamily':
-getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk, L2Fam)
-## S4 method for signature 'IC, asMSE, UncondNeighborhood,
-## missing':
-getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, asMSE, UncondNeighborhood,
-## L2ParamFamily':
-getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'TotalVarIC, asUnOvShoot,
-## UncondNeighborhood, missing':
-getRiskIC(IC, risk, neighbor)
-
-## S4 method for signature 'IC, fiUnOvShoot,
-## ContNeighborhood, missing':
-getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
-
-## S4 method for signature 'IC, fiUnOvShoot,
-## TotalVarNeighborhood, missing':
-getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
</pre>
@@ -92,32 +50,20 @@
object of class <code>"RiskType"</code>. </td></tr>
<tr valign="top"><td><code>neighbor</code></td>
<td>
-object of class <code>"Neighborhood"</code>. </td></tr>
-<tr valign="top"><td><code>L2Fam</code></td>
-<td>
-object of class <code>"L2ParamFamily"</code>. </td></tr>
+object of class <code>"Neighborhood"</code>; missing in the methods described here. </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
-<tr valign="top"><td><code>tol</code></td>
+<tr valign="top"><td><code>L2Fam</code></td>
<td>
-the desired accuracy (convergence tolerance).</td></tr>
-<tr valign="top"><td><code>sampleSize</code></td>
-<td>
-integer: sample size. </td></tr>
-<tr valign="top"><td><code>Algo</code></td>
-<td>
-"A" or "B". </td></tr>
-<tr valign="top"><td><code>cont</code></td>
-<td>
-"left" or "right". </td></tr>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
</table>
<h3>Details</h3>
<p>
To make sure that the results are valid, it is recommended
-to include an additional check of the IC properties of <code>IC</code>
+to include an additional check of the IC properties of <code>IC</code>
using <code>checkIC</code>.
</p>
@@ -130,44 +76,10 @@
<h3>Methods</h3>
<dl>
-<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
+<dt>IC = "HampIC", risk = "asCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code> read off from corresp. <code>Risks</code> slot. </dd>
-<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
-
-
-<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
-
-
-<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
-
-
-<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations. </dd>
-
-
-<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations and <code>L2Fam</code>. </dd>
-
-
-<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> in case of total variation neighborhoods. </dd>
-
-
-<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code> in case of total variation
-neighborhoods. </dd>
-
-
-<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic mean square error of <code>IC</code>. </dd>
-
-
-<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic mean square error of <code>IC</code> under <code>L2Fam</code>. </dd>
-
-
-<dt>IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic under-/overshoot risk of <code>IC</code>. </dd>
-
-
-<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
-
-
-<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
+<dt>IC = "HampIC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code> read off from corresp. <code>Risks</code> slot. </dd>
</dl>
<h3>Note</h3>
@@ -180,7 +92,7 @@
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -197,11 +109,11 @@
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
<p>
-Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
of M-estimators on Neighborhoods.
</p>
@@ -209,7 +121,7 @@
<h3>See Also</h3>
<p>
-<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
+<code><a href="getRiskIC-methods.html">getRiskIC-methods</a></code>, <code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
</p>
<script Language="JScript">
Modified: pkg/ROptEst/chm/lowerCaseRadius.html
===================================================================
--- pkg/ROptEst/chm/lowerCaseRadius.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/lowerCaseRadius.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -10,6 +10,7 @@
<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,ANY-method">
<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,ANY-method">
<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,onesidedBias-method">
+<param name="keyword" value="R: lowerCaseRadius,UnivariateDistribution,ContNeighborhood,asMSE,onesidedBias-method">
<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,asymmetricBias-method">
<param name="keyword" value=" Computation of the lower case radius">
</object>
@@ -79,6 +80,11 @@
<dt>L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE",
biastype = "asymmetricBias"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"ContNeighborhood"</code>
for asymmetric bias.</dd>
+
+
+<dt>L2Fam = "UnivariateDistribution", neighbor = "ContNeighborhood", risk = "asMSE",
+biastype = "onesidedBias"</dt><dd>used only internally;
+trick to be able to call lower case radius from within minmax bias solver</dd>
</dl>
<h3>Author(s)</h3>
Modified: pkg/ROptEst/chm/minmaxBias.html
===================================================================
--- pkg/ROptEst/chm/minmaxBias.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/chm/minmaxBias.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -8,6 +8,7 @@
<param name="keyword" value="R: minmaxBias">
<param name="keyword" value="R: minmaxBias-methods">
<param name="keyword" value="R: minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: minmaxBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
<param name="keyword" value="R: minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
<param name="keyword" value="R: minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
<param name="keyword" value="R: minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method">
@@ -34,23 +35,28 @@
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, BiasType':
-minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+minmaxBias(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
## S4 method for signature 'UnivariateDistribution,
## ContNeighborhood, asymmetricBias':
-minmaxBias(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+minmaxBias(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, onesidedBias':
+minmaxBias(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
+
+## S4 method for signature 'UnivariateDistribution,
## TotalVarNeighborhood, BiasType':
-minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+minmaxBias(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
## S4 method for signature 'RealRandVariable,
## ContNeighborhood, BiasType':
-minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+minmaxBias(L2deriv, neighbor, biastype, Distr,
+ L2derivDistrSymm, z.start, A.start, trafo, maxiter, tol)
</pre>
@@ -77,18 +83,9 @@
<tr valign="top"><td><code>symm</code></td>
<td>
logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
-<tr valign="top"><td><code>DistrSymm</code></td>
-<td>
-object of class <code>"DistributionSymmetry"</code>. </td></tr>
-<tr valign="top"><td><code>L2derivSymm</code></td>
-<td>
-object of class <code>"FunSymmList"</code>. </td></tr>
<tr valign="top"><td><code>L2derivDistrSymm</code></td>
<td>
object of class <code>"DistrSymmList"</code>. </td></tr>
-<tr valign="top"><td><code>Finfo</code></td>
-<td>
-Fisher information matrix. </td></tr>
<tr valign="top"><td><code>z.start</code></td>
<td>
initial value for the centering constant. </td></tr>
@@ -98,18 +95,12 @@
<tr valign="top"><td><code>trafo</code></td>
<td>
matrix: transformation of the parameter. </td></tr>
-<tr valign="top"><td><code>upper</code></td>
-<td>
-upper bound for the optimal clipping bound. </td></tr>
<tr valign="top"><td><code>maxiter</code></td>
<td>
the maximum number of iterations. </td></tr>
<tr valign="top"><td><code>tol</code></td>
<td>
the desired accuracy (convergence tolerance).</td></tr>
-<tr valign="top"><td><code>warn</code></td>
-<td>
-logical: print warnings. </td></tr>
</table>
<h3>Value</h3>
Added: pkg/ROptEst/chm/updateNorm-methods.html
===================================================================
--- pkg/ROptEst/chm/updateNorm-methods.html (rev 0)
+++ pkg/ROptEst/chm/updateNorm-methods.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,136 @@
+<html><head><title>Methods for Function updateNorm in Package ‘ROptEst’</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>updateNorm-methods(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: updateNorm-methods">
+<param name="keyword" value="R: updateNorm">
+<param name="keyword" value="R: updateNorm,NormType-method">
+<param name="keyword" value="R: updateNorm,InfoNorm-method">
+<param name="keyword" value="R: updateNorm,SelfNorm-method">
+<param name="keyword" value=" Methods for Function updateNorm in Package ‘ROptEst’">
+</object>
+
+
+<h2>Methods for Function updateNorm in Package ‘ROptEst’</h2>
+
+
+<h3>Description</h3>
+
+<p>
+updateNorm-methods to update norm in IC-Algo
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>updateNorm(normtype, ...)
+## S4 method for signature 'NormType':
+updateNorm(normtype, ...)
+## S4 method for signature 'InfoNorm':
+updateNorm(normtype, FI, ...)
+## S4 method for signature 'SelfNorm':
+updateNorm(normtype, L2, neighbor, biastype, Distr, V.comp,
+ cent, stand, w, ...)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>normtype</code></td>
+<td>
+normtype of class <code>NormType</code></td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+further arguments to be passed to specific methods.</td></tr>
+<tr valign="top"><td><code>FI</code></td>
+<td>
+matrix: Fisher Information</td></tr>
+<tr valign="top"><td><code>L2</code></td>
+<td>
+L2derivative</td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>V.comp</code></td>
+<td>
+matrix: indication which components of the standardizing
+matrix have to be computed. </td></tr>
+<tr valign="top"><td><code>w</code></td>
+<td>
+object of class <code>RobWeight</code>; current weight</td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+<code>updateNorm</code> is used internally in the opt-IC-algorithm to be
+able to work with a norm that depends on the Fisher information at a certain
+parameter (<code>InfoType</code>) or on the current covariance (<code>SelfNorm</code>)
+</p>
+
+
+<h3>Value</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>updateNorm</code></td>
+<td>
+</td></tr>
+</table>
+<p>
+ an updated object of class <code>NormType</code></p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>updateNorm</dt><dd><code>signature(normtype = "NormType")</code>: leaves the norm unchanged;</dd>
+<dt>updateNorm</dt><dd><code>signature(normtype = "InfoNorm")</code>:
+udates the norm in the information-standardized case; just used
+internally in the opt-IC-Algorithm. </dd>
+<dt>updateNorm</dt><dd><code>signature(normtype = "SelfNorm")</code>:
+udates the norm in the self-standardized case; just used
+internally in the opt-IC-Algorithm. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'NormType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">NormType-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/ROptEst/man/getAsRisk.Rd
===================================================================
--- pkg/ROptEst/man/getAsRisk.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getAsRisk.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,19 +1,19 @@
\name{getAsRisk}
\alias{getAsRisk}
\alias{getAsRisk-methods}
-\alias{getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method}
-\alias{getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method}
-\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,asMSE,UnivariateDistribution,Neighborhood,ANY-method}
+\alias{getAsRisk,asMSE,EuclRandVariable,Neighborhood,ANY-method}
+\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,ANY-method}
\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method}
\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
-\alias{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
-\alias{getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method}
-\alias{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method}
-\alias{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
-\alias{getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method}
-\alias{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method}
-\alias{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method}
-\alias{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method}
+\alias{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,ANY-method}
+\alias{getAsRisk,asBias,RealRandVariable,ContNeighborhood,ANY-method}
+\alias{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,ANY-method}
+\alias{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,ANY-method}
+\alias{getAsRisk,asCov,RealRandVariable,ContNeighborhood,ANY-method}
+\alias{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,ANY-method}
+\alias{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,ANY-method}
+\alias{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY-method}
\alias{getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method}
\title{Generic Function for Computation of Asymptotic Risks}
@@ -25,32 +25,32 @@
\usage{
getAsRisk(risk, L2deriv, neighbor, biastype, ...)
-\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
-\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo, norm = EuclideanNorm)
+\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo, norm = EuclideanNorm)
-\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, trafo)
\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,onesidedBias}(risk, L2deriv, neighbor, biastype, trafo)
\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias}(risk, L2deriv, neighbor, biastype, trafo)
-\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, trafo)
-\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
+\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
z.start, A.start, maxiter, tol, norm = EuclideanNorm)
-\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
+\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
-\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
+\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, norm = EuclideanNorm)
-\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
\S4method{getAsRisk}{asSemivar,UnivariateDistribution,Neighborhood,onesidedBias}(risk, L2deriv, neighbor, biastype,
clip, cent, stand, trafo)
@@ -60,7 +60,7 @@
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability distributions. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
- \item{biastype}{ object of class \code{"BiasType"}. }
+ \item{biastype}{ object of class \code{"ANY"}. }
\item{\dots}{ additional parameters. }
\item{clip}{ optimal clipping bound. }
\item{cent}{ optimal centering constant. }
@@ -78,15 +78,15 @@
\value{The asymptotic risk is computed.}
\section{Methods}{
\describe{
- \item{risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":}{
+ \item{risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "ANY":}{
computes asymptotic mean square error in methods for
function \code{getInfRobIC}. }
- \item{risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":}{
+ \item{risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "ANY":}{
computes asymptotic mean square error in methods for
function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "ANY":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
\item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias":}{
@@ -95,30 +95,30 @@
\item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "ANY":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "ANY":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "ANY":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":}{
+ \item{risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "ANY":}{
computes trace of asymptotic covariance in methods
for function \code{getInfRobIC}. }
- \item{risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
+ \item{risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "ANY":}{
computes trace of asymptotic covariance in methods for
function \code{getInfRobIC}. }
- \item{risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":}{
+ \item{risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "ANY":}{
computes asymptotic under-/overshoot risk in methods for
function \code{getInfRobIC}. }
Modified: pkg/ROptEst/man/getBiasIC.Rd
===================================================================
--- pkg/ROptEst/man/getBiasIC.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getBiasIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,7 +1,8 @@
\name{getBiasIC}
+\docType{methods}
\alias{getBiasIC}
\alias{getBiasIC-methods}
-\alias{getBiasIC,IC,UncondNeighborhood-method}
+\alias{getBiasIC,HampIC,UncondNeighborhood-method}
\title{Generic function for the computation of the asymptotic bias for an IC}
\description{
@@ -10,42 +11,36 @@
\usage{
getBiasIC(IC, neighbor, ...)
-\S4method{getBiasIC}{IC,UncondNeighborhood}(IC, neighbor, L2Fam,
- biastype = symmetricBias(),
- tol = .Machine$double.eps^0.25)
-
+\S4method{getBiasIC}{HampIC,UncondNeighborhood}(IC, neighbor, L2Fam)
}
\arguments{
\item{IC}{ object of class \code{"InfluenceCurve"} }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
\item{\dots}{ additional parameters }
- \item{L2Fam}{ object of class \code{"L2ParamFamily"} or missing. }
- \item{biastype}{ object of class \code{"BiasType"}. }
- \item{tol}{ the desired accuracy (convergence tolerance).}
}
-\details{To make sure that the results are valid, it is recommended
- to include an additional check of the IC properties of \code{IC}
- using \code{checkIC}.}
-\value{The asymptotic bias of an IC is computed.}
+\details{}
+\value{The bias of the IC is computed.}
\section{Methods}{
\describe{
-
- \item{IC = "IC", neighbor = "UncondNeighborhood":}{
- asymptotic bias of \code{IC} in case of unconditional neighborhoods. }
-
+ \item{IC = "HampIC", neighbor = "UncondNeighborhood"}{
+ reads off the as. bias from the risks-slot of the IC. }
}}
\references{
+ Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+ Verw. Geb. \bold{10}:269--278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
- Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
- Mathematical Methods in Statistics \emph{14}(1), 105-131.
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Bias
+ of M-estimators on Neighborhoods.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
- Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
-
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
\note{This generic function is still under construction.}
\seealso{\code{\link{getRiskIC-methods}}, \code{\link[RobAStBase]{InfRobModel-class}}}
%\examples{}
Modified: pkg/ROptEst/man/getInfCent.Rd
===================================================================
--- pkg/ROptEst/man/getInfCent.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfCent.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -19,19 +19,19 @@
getInfCent(L2deriv, neighbor, biastype, ...)
\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
\S4method{getInfCent}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
\S4method{getInfCent}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+ neighbor, biastype, z.comp, stand, cent, clip, w)
\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,onesidedBias}(L2deriv,
- neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv,
- neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
+ neighbor, biastype, clip, cent, tol.z, symm, trafo)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
@@ -47,6 +47,7 @@
\item{trafo}{ matrix: transformation of the parameter. }
\item{z.comp}{ logical vector: indication which components of the
centering constant have to be computed. }
+ \item{w}{object of class \code{RobWeight}; current weight}
}
%\details{}
\value{The optimal centering constant is computed.}
Modified: pkg/ROptEst/man/getInfClip.Rd
===================================================================
--- pkg/ROptEst/man/getInfClip.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfClip.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -24,7 +24,7 @@
\S4method{getInfClip}{numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
-\S4method{getInfClip}{numeric,UnivariateDistribution,asSemivar,ContNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+\S4method{getInfClip}{numeric,UnivariateDistribution,asSemivar,ContNeighborhood}(clip, L2deriv, risk, neighbor, cent, symm, trafo)
}
\arguments{
\item{clip}{ positive real: clipping bound }
Modified: pkg/ROptEst/man/getInfGamma.Rd
===================================================================
--- pkg/ROptEst/man/getInfGamma.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfGamma.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -18,22 +18,22 @@
getInfGamma(L2deriv, risk, neighbor, biastype, ...)
\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,BiasType}(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
\S4method{getInfGamma}{UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType}(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
\S4method{getInfGamma}{RealRandVariable,asMSE,ContNeighborhood,BiasType}(L2deriv,
- risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
+ risk, neighbor, biastype, Distr, stand, cent, clip)
\S4method{getInfGamma}{UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType}(L2deriv,
- risk, neighbor, biastype = symmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias}(L2deriv,
- risk, neighbor, biastype = positiveBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias}(L2deriv,
- risk, neighbor, biastype = asymmetricBias(), cent, clip)
+ risk, neighbor, biastype, cent, clip)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
Modified: pkg/ROptEst/man/getInfRobIC.Rd
===================================================================
--- pkg/ROptEst/man/getInfRobIC.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfRobIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -27,11 +27,11 @@
\S4method{getInfRobIC}{RealRandVariable,asCov,ContNeighborhood}(L2deriv, risk, neighbor, Distr, Finfo, trafo)
-\S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+\S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv, risk, neighbor, symm, trafo,
+ maxiter, tol)
-\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk, neighbor, Distr,
+ L2derivDistrSymm, z.start, A.start, trafo, maxiter, tol)
\S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
upper, maxiter, tol, warn)
Modified: pkg/ROptEst/man/getInfStand.Rd
===================================================================
--- pkg/ROptEst/man/getInfStand.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfStand.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -17,19 +17,19 @@
getInfStand(L2deriv, neighbor, biastype, ...)
\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
\S4method{getInfStand}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
\S4method{getInfStand}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+ neighbor, biastype, Distr, A.comp, stand, clip, cent, trafo, w)
\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = positiveBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
- neighbor, biastype = asymmetricBias(), clip, cent, trafo)
+ neighbor, biastype, clip, cent, trafo)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
@@ -44,6 +44,7 @@
\item{trafo}{ matrix: transformation of the parameter. }
\item{A.comp}{ matrix: indication which components of the standardizing
matrix have to be computed. }
+ \item{w}{object of class \code{RobWeight}; current weight}
}
%\details{}
\value{The standardizing matrix is computed.}
Modified: pkg/ROptEst/man/getInfV.Rd
===================================================================
--- pkg/ROptEst/man/getInfV.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getInfV.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -3,7 +3,7 @@
\alias{getInfV-methods}
\alias{getInfV,UnivariateDistribution,ContNeighborhood,BiasType-method}
\alias{getInfV,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
-\alias{getInfV,EuclRandVariable,ContNeighborhood,BiasType-method}
+\alias{getInfV,RealRandVariable,ContNeighborhood,BiasType-method}
\alias{getInfV,UnivariateDistribution,ContNeighborhood,onesidedBias-method}
\alias{getInfV,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
@@ -14,17 +14,32 @@
directly. It is used to compute optimally robust ICs.
}
\usage{
-getInfV(L2deriv, neighbor, biastype, clip, cent, stand)
+getInfV(L2deriv, neighbor, biastype, ...)
+\S4method{getInfV}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+\S4method{getInfV}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+\S4method{getInfV}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype, Distr, V.comp, cent, stand,
+ w)
+\S4method{getInfV}{UnivariateDistribution,ContNeighborhood,onesidedBias}(L2deriv,
+ neighbor, biastype, clip, cent, stand)
+\S4method{getInfV}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv,
+ neighbor, biastype, clip, cent, stand)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability measures. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{\dots}{ additional parameters. }
- \item{biastype}{ object of class \code{"BiasType"} }
\item{clip}{ positive real: clipping bound }
\item{cent}{ optimal centering constant. }
\item{stand}{ standardizing matrix. }
+ \item{Distr}{ standardizing matrix. }
+ \item{V.comp}{ matrix: indication which components of the standardizing
+ matrix have to be computed. }
+ \item{w}{object of class \code{RobWeight}; current weight}
}
%\details{}
\value{The asymptotic variance of an ALE to IC of Hampel type is computed.}
@@ -39,8 +54,7 @@
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
- Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
\seealso{\code{\link[RobAStBase]{ContIC-class}}, \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
Modified: pkg/ROptEst/man/getL1normL2deriv.Rd
===================================================================
--- pkg/ROptEst/man/getL1normL2deriv.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getL1normL2deriv.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -13,7 +13,7 @@
cent, ...)
\S4method{getL1normL2deriv}{UnivariateDistribution}(L2deriv,
- cent, stand, Distr, ...)
+ cent, stand, Distr, normtype, ...)
}
%\details{}
@@ -22,7 +22,8 @@
\item{cent}{centering Lagrange Multiplier}
\item{stand}{standardizing Lagrange Multiplier}
\item{Distr}{distribution of the L2derivative}
- \item{...}{further arguments (not used at the moment)}
+ \item{normtype}{object of class \code{NormType}; the norm under which we work}
+ \item{\dots}{further arguments (not used at the moment)}
}
\value{L1 norm of the L2derivative}
Modified: pkg/ROptEst/man/getRiskIC.Rd
===================================================================
--- pkg/ROptEst/man/getRiskIC.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/getRiskIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,17 +1,9 @@
\name{getRiskIC}
+\docType{methods}
\alias{getRiskIC}
\alias{getRiskIC-methods}
-\alias{getRiskIC,IC,asCov,missing,missing-method}
-\alias{getRiskIC,IC,asCov,missing,L2ParamFamily-method}
-\alias{getRiskIC,IC,trAsCov,missing,missing-method}
-\alias{getRiskIC,IC,trAsCov,missing,L2ParamFamily-method}
-\alias{getRiskIC,IC,asBias,UncondNeighborhood,missing-method}
-\alias{getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method}
-\alias{getRiskIC,IC,asMSE,UncondNeighborhood,missing-method}
-\alias{getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method}
-\alias{getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method}
-\alias{getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method}
-\alias{getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method}
+\alias{getRiskIC,HampIC,asCov,missing,missing-method}
+\alias{getRiskIC,HampIC,asCov,missing,L2ParamFamily-method}
\title{Generic function for the computation of a risk for an IC}
\description{
@@ -20,84 +12,29 @@
\usage{
getRiskIC(IC, risk, neighbor, L2Fam, ...)
-\S4method{getRiskIC}{IC,asCov,missing,missing}(IC, risk, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{HampIC,asCov,missing,missing}(IC, risk)
-\S4method{getRiskIC}{IC,asCov,missing,L2ParamFamily}(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{HampIC,asCov,missing,L2ParamFamily}(IC, risk, L2Fam)
-\S4method{getRiskIC}{IC,trAsCov,missing,missing}(IC, risk, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,trAsCov,missing,L2ParamFamily}(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{TotalVarIC,asUnOvShoot,UncondNeighborhood,missing}(IC, risk, neighbor)
-
-\S4method{getRiskIC}{IC,fiUnOvShoot,ContNeighborhood,missing}(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
-
-\S4method{getRiskIC}{IC,fiUnOvShoot,TotalVarNeighborhood,missing}(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
}
\arguments{
\item{IC}{ object of class \code{"InfluenceCurve"} }
\item{risk}{ object of class \code{"RiskType"}. }
- \item{neighbor}{ object of class \code{"Neighborhood"}. }
- \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}; missing in the methods described here. }
\item{\dots}{ additional parameters }
- \item{tol}{ the desired accuracy (convergence tolerance).}
- \item{sampleSize}{ integer: sample size. }
- \item{Algo}{ "A" or "B". }
- \item{cont}{ "left" or "right". }
+ \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
}
\details{To make sure that the results are valid, it is recommended
- to include an additional check of the IC properties of \code{IC}
+ to include an additional check of the IC properties of \code{IC}
using \code{checkIC}.}
\value{The risk of an IC is computed.}
\section{Methods}{
\describe{
- \item{IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"}{
- asymptotic covariance of \code{IC}. }
+ \item{IC = "HampIC", risk = "asCov", neighbor = "missing", L2Fam = "missing"}{
+ asymptotic covariance of \code{IC} read off from corresp. \code{Risks} slot. }
- \item{IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"}{
- asymptotic covariance of \code{IC} under \code{L2Fam}. }
-
- \item{IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"}{
- asymptotic covariance of \code{IC}. }
-
- \item{IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"}{
- asymptotic covariance of \code{IC} under \code{L2Fam}. }
-
- \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"}{
- asymptotic bias of \code{IC} under convex contaminations. }
-
- \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"}{
- asymptotic bias of \code{IC} under convex contaminations and \code{L2Fam}. }
-
- \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"}{
- asymptotic bias of \code{IC} in case of total variation neighborhoods. }
-
- \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"}{
- asymptotic bias of \code{IC} under \code{L2Fam} in case of total variation
- neighborhoods. }
-
- \item{IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"}{
- asymptotic mean square error of \code{IC}. }
-
- \item{IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"}{
- asymptotic mean square error of \code{IC} under \code{L2Fam}. }
-
- \item{IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"}{
- asymptotic under-/overshoot risk of \code{IC}. }
-
- \item{IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"}{
- finite-sample under-/overshoot risk of \code{IC}. }
-
- \item{IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"}{
- finite-sample under-/overshoot risk of \code{IC}. }
+ \item{IC = "HampIC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"}{
+ asymptotic covariance of \code{IC} under \code{L2Fam} read off from corresp. \code{Risks} slot. }
}}
\references{
Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
@@ -107,15 +44,15 @@
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
- Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
of M-estimators on Neighborhoods.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
\note{This generic function is still under construction.}
-\seealso{\code{\link{getRiskIC-methods}}, \code{\link[RobAStBase]{InfRobModel-class}}}
+\seealso{\code{\link[ROptEst]{getRiskIC-methods}}, \code{\link[RobAStBase]{InfRobModel-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/minmaxBias.Rd
===================================================================
--- pkg/ROptEst/man/minmaxBias.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/ROptEst/man/minmaxBias.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -2,6 +2,7 @@
\alias{minmaxBias}
\alias{minmaxBias-methods}
\alias{minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{minmaxBias,UnivariateDistribution,ContNeighborhood,onesidedBias-method}
\alias{minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
\alias{minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
\alias{minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method}
@@ -15,18 +16,21 @@
\usage{
minmaxBias(L2deriv, neighbor, biastype, ...)
-\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
-\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
-\S4method{minmaxBias}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
- upper, maxiter, tol, warn)
+\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,onesidedBias}(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
-\S4method{minmaxBias}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+\S4method{minmaxBias}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv, neighbor, biastype, symm, trafo,
+ maxiter, tol)
+\S4method{minmaxBias}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype, Distr,
+ L2derivDistrSymm, z.start, A.start, trafo, maxiter, tol)
+
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
@@ -36,17 +40,12 @@
\item{\dots}{ additional parameters. }
\item{Distr}{ object of class \code{"Distribution"}. }
\item{symm}{ logical: indicating symmetry of \code{L2deriv}. }
- \item{DistrSymm}{ object of class \code{"DistributionSymmetry"}. }
- \item{L2derivSymm}{ object of class \code{"FunSymmList"}. }
\item{L2derivDistrSymm}{ object of class \code{"DistrSymmList"}. }
- \item{Finfo}{ Fisher information matrix. }
\item{z.start}{ initial value for the centering constant. }
\item{A.start}{ initial value for the standardizing matrix. }
\item{trafo}{ matrix: transformation of the parameter. }
- \item{upper}{ upper bound for the optimal clipping bound. }
\item{maxiter}{ the maximum number of iterations. }
\item{tol}{ the desired accuracy (convergence tolerance).}
- \item{warn}{ logical: print warnings. }
}
%\details{}
\value{The bias-optimally robust IC is computed.}
Added: pkg/ROptEst/man/updateNorm-methods.Rd
===================================================================
--- pkg/ROptEst/man/updateNorm-methods.Rd (rev 0)
+++ pkg/ROptEst/man/updateNorm-methods.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,55 @@
+\name{updateNorm-methods}
+\docType{methods}
+\alias{updateNorm-methods}
+\alias{updateNorm}
+\alias{updateNorm,NormType-method}
+\alias{updateNorm,InfoNorm-method}
+\alias{updateNorm,SelfNorm-method}
+\title{ Methods for Function updateNorm in Package `ROptEst' }
+
+\description{updateNorm-methods to update norm in IC-Algo}
+
+\usage{updateNorm(normtype, ...)
+\S4method{updateNorm}{NormType}(normtype, ...)
+\S4method{updateNorm}{InfoNorm}(normtype, FI, ...)
+\S4method{updateNorm}{SelfNorm}(normtype, L2, neighbor, biastype, Distr, V.comp,
+ cent, stand, w, ...)
+}
+
+\arguments{
+ \item{normtype}{normtype of class \code{NormType}}
+ \item{\dots}{ further arguments to be passed to specific methods.}
+ \item{FI}{matrix: Fisher Information}
+ \item{L2}{L2derivative}
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"} }
+ \item{cent}{ optimal centering constant. }
+ \item{stand}{ standardizing matrix. }
+ \item{Distr}{ standardizing matrix. }
+ \item{V.comp}{ matrix: indication which components of the standardizing
+ matrix have to be computed. }
+ \item{w}{object of class \code{RobWeight}; current weight}
+}
+\section{Methods}{\describe{
+\item{updateNorm}{\code{signature(normtype = "NormType")}: leaves the norm unchanged;}
+\item{updateNorm}{\code{signature(normtype = "InfoNorm")}:
+ udates the norm in the information-standardized case; just used
+ internally in the opt-IC-Algorithm. }
+\item{updateNorm}{\code{signature(normtype = "SelfNorm")}:
+ udates the norm in the self-standardized case; just used
+ internally in the opt-IC-Algorithm. }
+}}
+\value{
+\item{updateNorm} an updated object of class \code{NormType}
+}
+
+\details{\code{updateNorm} is used internally in the opt-IC-algorithm to be
+ able to work with a norm that depends on the Fisher information at a certain
+ parameter (\code{InfoType}) or on the current covariance (\code{SelfNorm})}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+\seealso{\code{\link[distrMod]{NormType-class}}}
+%\examples{}
+\concept{asymptotic risk}
+\concept{risk}
+\keyword{classes}
+
Modified: pkg/RobAStBase/NAMESPACE
===================================================================
--- pkg/RobAStBase/NAMESPACE 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/NAMESPACE 2008-03-28 02:21:40 UTC (rev 80)
@@ -11,7 +11,7 @@
"FixRobModel",
"InfRobModel")
exportClasses("InfluenceCurve",
- "IC",
+ "IC", "HampIC",
"ContIC",
"TotalVarIC")
exportClasses("RobAStControl", "RobWeight", "BoundedWeight",
@@ -47,7 +47,9 @@
"getweight", "minbiasweight",
"generateIC.fct",
"makeIC")
+exportMethods("getRiskIC")
+exportMethods("getBiasIC")
export("ContNeighborhood", "TotalVarNeighborhood")
export("FixRobModel", "InfRobModel")
export("InfluenceCurve", "IC", "ContIC", "TotalVarIC")
-export("EuclideanNorm", "QuadFormNorm")
+export(".eq", ".getDistr")
Modified: pkg/RobAStBase/R/AllClass.R
===================================================================
--- pkg/RobAStBase/R/AllClass.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/AllClass.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -104,16 +104,42 @@
return(TRUE)
})
-# (partial) influence curve of contamination type
-setClass("ContIC",
- representation(clip = "numeric",
- cent = "numeric",
- stand = "matrix",
+# HampIC -- common mother class to ContIC and TotalVarIC
+setClass("HampIC",
+ representation(stand = "matrix",
lowerCase = "OptionalNumeric",
neighborRadius = "numeric",
- weight = "HampelWeight",
+ weight = "RobWeight",
biastype = "BiasType",
normtype = "NormType"),
+ prototype(name = "IC of total-var or contamination type",
+ Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x}),
+ Domain = Reals())),
+ Risks = list(), weight = new("RobWeight"),
+ Infos = matrix(c(character(0),character(0)), ncol=2,
+ dimnames=list(character(0), c("method", "message"))),
+ CallL2Fam = call("L2ParamFamily"),
+ stand = as.matrix(1),
+ lowerCase = NULL,
+ neighborRadius = 0,
+ biastype = symmetricBias(),
+ NormType = NormType()),
+ contains = "IC",
+ validity = function(object){
+ if(any(object at neighborRadius < 0)) # radius vector?!
+ stop("'neighborRadius' has to be in [0, Inf]")
+ if(!is.null(object at lowerCase))
+ if(length(object at lowerCase) != nrow(object at stand))
+ stop("length of 'lowerCase' != nrow of standardizing matrix")
+ L2Fam <- eval(object at CallL2Fam)
+ if(!identical(dim(L2Fam at param@trafo), dim(object at stand)))
+ stop(paste("dimension of 'trafo' of 'param' != dimension of 'stand'"))
+ return(TRUE)
+ })
+# (partial) influence curve of contamination type
+setClass("ContIC",
+ representation(clip = "numeric",
+ cent = "numeric"),
prototype(name = "IC of contamination type",
Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x}),
Domain = Reals())),
@@ -125,7 +151,7 @@
lowerCase = NULL,
neighborRadius = 0, weight = new("HampelWeight"),
biastype = symmetricBias(), NormType = NormType()),
- contains = "IC",
+ contains = "HampIC",
validity = function(object){
if(any(object at neighborRadius < 0)) # radius vector?!
stop("'neighborRadius' has to be in [0, Inf]")
@@ -137,6 +163,8 @@
if(length(object at lowerCase) != nrow(object at stand))
stop("length of 'lowerCase' != nrow of standardizing matrix")
L2Fam <- eval(object at CallL2Fam)
+ if(!is(weight,"HampelWeight"))
+ stop("Weight has to be of class 'HampelWeight'")
if(!identical(dim(L2Fam at param@trafo), dim(object at stand)))
stop(paste("dimension of 'trafo' of 'param' != dimension of 'stand'"))
return(TRUE)
@@ -144,11 +172,7 @@
# (partial) influence curve of total variation type
setClass("TotalVarIC",
representation(clipLo = "numeric",
- clipUp = "numeric",
- stand = "matrix",
- lowerCase = "OptionalNumeric",
- neighborRadius = "numeric",
- weight = "BdStWeight"),
+ clipUp = "numeric"),
prototype(name = "IC of total variation type",
Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x}),
Domain = Reals())),
@@ -159,7 +183,7 @@
clipLo = -Inf, clipUp = Inf, stand = as.matrix(1),
lowerCase = NULL,
neighborRadius = 0, weight = new("BdStWeight")),
- contains = "IC",
+ contains = "HampIC",
validity = function(object){
if(any(object at neighborRadius < 0)) # radius vector?!
stop("'neighborRadius' has to be in [0, Inf]")
@@ -168,6 +192,8 @@
if((length(object at clipLo) != 1) && (length(object at clipLo) != length(object at Curve)))
stop("length of upper clipping bound != 1 and != length of 'Curve'")
L2Fam <- eval(object at CallL2Fam)
+ if(!is(weight,"BdStWeight"))
+ stop("Weight has to be of class 'BdStWeight'")
if(!identical(dim(L2Fam at param@trafo), dim(object at stand)))
stop(paste("dimension of 'trafo' of 'param' != dimension of 'stand'"))
return(TRUE)
Modified: pkg/RobAStBase/R/AllGeneric.R
===================================================================
--- pkg/RobAStBase/R/AllGeneric.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/AllGeneric.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -154,3 +154,15 @@
if(!isGeneric("generateIC.fct")){
setGeneric("generateIC.fct", function(neighbor, L2Fam, ...) standardGeneric("generateIC.fct"))
}
+if(!isGeneric("getRiskIC")){
+ setGeneric("getRiskIC",
+ function(IC, risk, neighbor, L2Fam, ...) standardGeneric("getRiskIC"))
+}
+if(!isGeneric("getBiasIC")){
+ setGeneric("getBiasIC",
+ function(IC, neighbor, ...) standardGeneric("getBiasIC"))
+}
+if(!isGeneric(".evalBiasIC")){
+ setGeneric(".evalBiasIC",
+ function(IC, neighbor, biastype, ...) standardGeneric(".evalBiasIC"))
+}
Modified: pkg/RobAStBase/R/ContIC.R
===================================================================
--- pkg/RobAStBase/R/ContIC.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/ContIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,6 +1,7 @@
## Generating function
ContIC <- function(name, CallL2Fam = call("L2ParamFamily"),
- Curve = EuclRandVarList(RealRandVariable(Map = c(function(x){x}), Domain = Reals())),
+ Curve = EuclRandVarList(RealRandVariable(Map = c(function(x){x}),
+ Domain = Reals())),
Risks, Infos, clip = Inf, cent = 0, stand = as.matrix(1),
lowerCase = NULL, neighborRadius = 0, w = new("HampelWeight"),
normtype = NormType(), biastype = symmetricBias()){
@@ -89,14 +90,9 @@
})
## Access methods
-setMethod("biastype", "ContIC", function(object) object at biastype)
-setMethod("normtype", "ContIC", function(object) object at normtype)
+
setMethod("clip", "ContIC", function(object) object at clip)
setMethod("cent", "ContIC", function(object) object at cent)
-setMethod("stand", "ContIC", function(object) object at stand)
-setMethod("weight", "ContIC", function(object) object at weight)
-setMethod("lowerCase", "ContIC", function(object) object at lowerCase)
-setMethod("neighborRadius", "ContIC", function(object) object at neighborRadius)
## replace methods
setReplaceMethod("clip", "ContIC",
@@ -147,15 +143,6 @@
addInfo(object) <- c("lowerCase<-", "The entries in 'Risks' and 'Infos' may be wrong")
object
})
-setReplaceMethod("neighborRadius", "ContIC",
- function(object, value){
- object at neighborRadius <- value
- if(any(value < 0)) # radius vector?!
- stop("'value' has to be in [0, Inf]")
- addInfo(object) <- c("neighborRadius<-", "The slot 'neighborRadius' has been changed")
- addInfo(object) <- c("neighborRadius<-", "The entries in 'Risks' and 'Infos' may be wrong")
- object
- })
setReplaceMethod("CallL2Fam", "ContIC",
function(object, value){
L2Fam <- eval(value)
Added: pkg/RobAStBase/R/HampIC.R
===================================================================
--- pkg/RobAStBase/R/HampIC.R (rev 0)
+++ pkg/RobAStBase/R/HampIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,20 @@
+### HampIC is only used internally; so no generating function exists;
+
+## Access methods
+setMethod("biastype", "HampIC", function(object) object at biastype)
+setMethod("normtype", "HampIC", function(object) object at normtype)
+setMethod("stand", "HampIC", function(object) object at stand)
+setMethod("weight", "HampIC", function(object) object at weight)
+setMethod("lowerCase", "HampIC", function(object) object at lowerCase)
+setMethod("neighborRadius", "HampIC", function(object) object at neighborRadius)
+
+setReplaceMethod("neighborRadius", "HampIC",
+ function(object, value){
+ object at neighborRadius <- value
+ if(any(value < 0)) # radius vector?!
+ stop("'value' has to be in [0, Inf]")
+ addInfo(object) <- c("neighborRadius<-", "The slot 'neighborRadius' has been changed")
+ addInfo(object) <- c("neighborRadius<-", "The entries in 'Risks' and 'Infos' may be wrong")
+ object
+ })
+
Modified: pkg/RobAStBase/R/IC.R
===================================================================
--- pkg/RobAStBase/R/IC.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/IC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -50,24 +50,7 @@
setMethod("checkIC", signature(IC = "IC", L2Fam = "missing"),
function(IC, out = TRUE){
L2Fam <- eval(IC at CallL2Fam)
- trafo <- trafo(L2Fam at param)
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
-
- cent <- E(L2Fam, IC1)
- if(out)
- cat("precision of centering:\t", cent, "\n")
-
- dims <- length(L2Fam at param)
- L2deriv <- as(diag(dims) %*% L2Fam at L2deriv, "EuclRandVariable")
- consist <- E(L2Fam, IC1 %*% t(L2deriv)) - trafo
- if(out){
- cat("precision of Fisher consistency:\n")
- print(consist)
- }
- prec <- max(abs(cent), abs(consist))
- names(prec) <- "maximum deviation"
-
- return(prec)
+ checkIC(IC, L2Fam)
})
## check centering and Fisher consistency
setMethod("checkIC", signature(IC = "IC", L2Fam = "L2ParamFamily"),
@@ -130,19 +113,7 @@
setMethod("makeIC", signature(IC = "IC", L2Fam = "missing"),
function(IC){
L2Fam <- eval(IC at CallL2Fam)
- trafo <- trafo(L2Fam at param)
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
-
- cent <- E(L2Fam, IC1)
-
- dims <- length(L2Fam at param)
- L2deriv <- as(diag(dims) %*% L2Fam at L2deriv, "EuclRandVariable")
- E1 <- matrix(E(L2Fam, as(IC1 %*% t(L2deriv),"EuclRandVariable")),
- nrow(trafo),dims)
- stand <- trafo %*% solve(E1)
- return(IC(name = name(IC),
- Curve = as(stand %*% (L2Fam at L2deriv - cent), "EuclRandVariable"),
- Risks="", Infos="", CallL2Fam = call(L2Fam)))
+ makeIC(IC, L2Fam)
})
## make some L2function a pIC at a model
@@ -157,12 +128,23 @@
cent <- E(D1, IC1)
dims <- length(L2Fam at param)
+ if(dimension(Domain(IC at Curve[[1]])) != dims)
+ stop("Dimension of IC and parameter must be the equal")
+
L2deriv <- as(diag(dims) %*% L2Fam at L2deriv, "EuclRandVariable")
- E1 <- matrix(E(L2Fam, as(IC1 %*% t(L2deriv),"EuclRandVariable")),
- nrow(trafo),dims)
+ E1 <- matrix(E(L2Fam, IC1 %*% t(L2deriv)), dims, dims)
+
stand <- trafo %*% solve(E1)
+ Y <- as(stand %*% L2Fam at L2deriv - cent, "EuclRandVariable")
+ ICfct <- vector(mode = "list", length = dims)
+ ICfct[[1]] <- function(x){Y(x)}
return(IC(name = name(IC),
- Curve = as(stand %*% (L2Fam at L2deriv - cent), "EuclRandVariable"),
- Risks="", Infos="", CallL2Fam = call(L2Fam)))
+ Curve = EuclRandVarList(EuclRandVariable(Map = ICfct,
+ Domain = Y at Domain,Range = Y at Range)),
+ Risks=list(), Infos=matrix(c("IC<-",
+ "generated by affine linear trafo to enforce consistency"), ncol=2,
+ dimnames=list(character(0), c("method", "message"))),
+ CallL2Fam = IC at CallL2Fam))
})
+
Modified: pkg/RobAStBase/R/TotalVarIC.R
===================================================================
--- pkg/RobAStBase/R/TotalVarIC.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/TotalVarIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -81,10 +81,6 @@
## Access methods
setMethod("clipLo", "TotalVarIC", function(object) object at clipLo)
setMethod("clipUp", "TotalVarIC", function(object) object at clipUp)
-setMethod("stand", "TotalVarIC", function(object) object at stand)
-setMethod("weight", "TotalVarIC", function(object) object at weight)
-setMethod("lowerCase", "TotalVarIC", function(object) object at lowerCase)
-setMethod("neighborRadius", "TotalVarIC", function(object) object at neighborRadius)
## Replace methods
setReplaceMethod("clipLo", "TotalVarIC",
@@ -135,15 +131,6 @@
addInfo(object) <- c("lowerCase<-", "The entries in 'Risks' and 'Infos' may be wrong")
object
})
-setReplaceMethod("neighborRadius", "TotalVarIC",
- function(object, value){
- object at neighborRadius <- value
- if(any(value < 0)) # radius vector?!
- stop("'value' has to be in [0, Inf]")
- addInfo(object) <- c("neighborRadius<-", "The slot 'neighborRadius' has been changed")
- addInfo(object) <- c("neighborRadius<-", "The entries in 'Risks' and 'Infos' may be wrong")
- object
- })
setReplaceMethod("CallL2Fam", "TotalVarIC",
function(object, value){
L2Fam <- eval(value)
Modified: pkg/RobAStBase/R/Weights.R
===================================================================
--- pkg/RobAStBase/R/Weights.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/Weights.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -21,8 +21,8 @@
setMethod("weight", "RobWeight", function(object) object at weight)
-setReplaceMethod("weight", "RobWeight", function(object,value)
- {object at weight <- value; object})
+setReplaceMethod("weight", "RobWeight", function(object,value)
+ {object at weight <- value; object})
setMethod("getweight",
signature(Weight = "HampelWeight", neighbor = "ContNeighborhood",
@@ -46,7 +46,7 @@
setMethod("getweight",
signature(Weight = "HampelWeight", neighbor = "ContNeighborhood",
biastype = "onesidedBias"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
z <- cent(Weight)
@@ -61,7 +61,7 @@
setMethod(getweight,
signature(Weight = "HampelWeight", neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
b1 <- b/nu(biastype)[1]
@@ -80,7 +80,7 @@
setMethod(getweight,
signature(Weight = "BdStWeight", neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
a <- A * cent(Weight)
@@ -115,7 +115,7 @@
setMethod(minbiasweight,
signature(Weight = "HampelWeight", neighbor = "ContNeighborhood",
biastype = "asymmetricBias"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
b1 <- b/nu(biastype)[1]
@@ -135,7 +135,7 @@
setMethod(minbiasweight,
signature(Weight = "HampelWeight", neighbor = "ContNeighborhood",
biastype = "onesidedBias"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
z <- cent(Weight)
@@ -152,7 +152,7 @@
setMethod(minbiasweight,
signature(Weight = "BdStWeight", neighbor = "TotalVarNeighborhood",
biastype = "BiasType"),# norm = "missing"),
- function(Weight, neighbor, biastype)
+ function(Weight, neighbor, biastype, ...)
{A <- stand(Weight)
b <- clip(Weight)
a <- A * cent(Weight)
Modified: pkg/RobAStBase/R/generateICfct.R
===================================================================
--- pkg/RobAStBase/R/generateICfct.R 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/R/generateICfct.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -8,9 +8,10 @@
d <- res$d
w <- weight(res$w)
nrvalues <- nrow(A)
+ dim <- ncol(A)
ICfct <- vector(mode = "list", length = nrvalues)
Y <- as(A %*% L2Fam at L2deriv - a, "EuclRandVariable")
- L <- as(L2Fam at L2deriv, "EuclRandVariable")
+ L <- as(diag(dim)%*%L2Fam at L2deriv, "EuclRandVariable")
if(nrvalues == 1){
if(!is.null(d)){
ICfct[[1]] <- function(x){}
Added: pkg/RobAStBase/R/getBiasIC.R
===================================================================
--- pkg/RobAStBase/R/getBiasIC.R (rev 0)
+++ pkg/RobAStBase/R/getBiasIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,79 @@
+###############################################################################
+## asymptotic Bias for various types
+###############################################################################
+setMethod("getBiasIC", signature(IC = "IC",
+ neighbor = "UncondNeighborhood"),
+ function(IC, neighbor, L2Fam, biastype = symmetricBias(),
+ normtype = NormType(), tol = .Machine$double.eps^0.25){
+ if(missing(L2Fam))
+ {misF <- TRUE; L2Fam <- eval(IC at CallL2Fam)}
+ D1 <- L2Fam at distribution
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(D1)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ x <- as.matrix(r(D1)(1e5))
+ x <- as.matrix(x[!duplicated(x),])
+
+ Bias <- .evalBiasIC(IC = IC, neighbor = neighbor, biastype = biastype,
+ normtype = normtype, x = x, trafo = L2Fam at param@trafo)
+
+ prec <- if(misF) checkIC(IC, out = FALSE) else
+ checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asBias = list(distribution = .getDistr(L2Fam),
+ neighborhood = neighbor at type, value = Bias)))
+ })
+
+
+### help functions ( not exported to namespace) for getRiskIC
+
+setMethod(".evalBiasIC", signature(IC = "IC",
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(IC, neighbor, biastype, normtype, x, trafo){
+ ICx <- evalRandVar(as(diag(dimension(IC at Curve)) %*% IC at Curve,
+ "EuclRandVariable"),x)
+
+ return(max(fct(normtype)(ICx)))}
+ )
+
+setMethod(".evalBiasIC", signature(IC = "IC",
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"),
+ function(IC, neighbor, biastype, normtype, x, trafo){
+ if(nrow(trafo) > 1)
+ stop("not yet implemented for dimension > 1")
+ IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
+ res <- evalRandVar(IC1, x)
+ return(max(res) - min(res))}
+ )
+
+setMethod(".evalBiasIC", signature(IC = "IC",
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"),
+ function(IC, neighbor, biastype, x, trafo){
+ if(nrow(trafo) > 1)
+ stop("not yet implemented for dimension > 1")
+ IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
+ res <- evalRandVar(IC1, x)
+ if (sign(biastype)>0)
+ return(max(res))
+ else return(-min(res))
+ })
+
+setMethod(".evalBiasIC", signature(IC = "IC",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(IC, neighbor, biastype, x, trafo){
+ if(nrow(trafo) > 1)
+ stop("not yet implemented for dimension > 1")
+ IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
+ res <- evalRandVar(IC1, x)
+ return(max(res)/nu(biastype)[2] -
+ min(res)/nu(biastype)[1])}
+ )
+
Added: pkg/RobAStBase/R/getRiskIC.R
===================================================================
--- pkg/RobAStBase/R/getRiskIC.R (rev 0)
+++ pkg/RobAStBase/R/getRiskIC.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,147 @@
+###############################################################################
+## asymptotic covariance
+###############################################################################
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asCov",
+ neighbor = "missing",
+ L2Fam = "missing"),
+ function(IC, risk, tol = .Machine$double.eps^0.25){
+ L2Fam <- eval(IC at CallL2Fam)
+
+ trafo <- L2Fam at param@trafo
+ IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
+
+ bias <- E(L2Fam, IC1)
+ Cov <- E(L2Fam, IC1 %*% t(IC1))
+
+ prec <- checkIC(IC, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asCov = list(distribution = .getDistr(L2Fam), value = Cov - bias %*% t(bias))))
+ })
+
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asCov",
+ neighbor = "missing",
+ L2Fam = "L2ParamFamily"),
+ function(IC, risk, L2Fam, tol = .Machine$double.eps^0.25){
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ trafo <- L2Fam at param@trafo
+ IC1 <- as(diag(dimension(IC at Curve)) %*% IC at Curve, "EuclRandVariable")
+
+ bias <- E(L2Fam, IC1)
+ Cov <- E(L2Fam, IC1 %*% t(IC1))
+
+ prec <- checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asCov = list(distribution = .getDistr(L2Fam), value = Cov - bias %*% t(bias))))
+ })
+
+###############################################################################
+## trace of asymptotic covariance
+###############################################################################
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "trAsCov",
+ neighbor = "missing",
+ L2Fam = "missing"),
+ function(IC, risk, tol = .Machine$double.eps^0.25){
+ trCov <- getRiskIC(IC, risk = asCov())$asCov
+ trCov$value <- sum(diag(trCov$value))
+
+ prec <- checkIC(IC, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(trAsCov = trCov))
+ })
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "trAsCov",
+ neighbor = "missing",
+ L2Fam = "L2ParamFamily"),
+ function(IC, risk, L2Fam, tol = .Machine$double.eps^0.25){
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ trCov <- getRiskIC(IC, risk = asCov(), L2Fam = L2Fam)$asCov
+ trCov$value <- sum(diag(trCov$value))
+
+ prec <- checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(trAsCov = trCov))
+ })
+
+###############################################################################
+## asymptotic Bias
+###############################################################################
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asBias",
+ neighbor = "UncondNeighborhood",
+ L2Fam = "missing"),
+ function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
+ getBiasIC(IC, neighbor, biastype(risk), normtype(risk), tol)
+ })
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asBias",
+ neighbor = "UncondNeighborhood",
+ L2Fam = "L2ParamFamily"),
+ function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
+ getBiasIC(IC, neighbor, L2Fam, biastype(risk), normtype(risk), tol)
+ })
+###############################################################################
+## asymptotic MSE
+###############################################################################
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asMSE",
+ neighbor = "UncondNeighborhood",
+ L2Fam = "missing"),
+ function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
+ L2fam <- eval(IC at CallL2Fam)
+ getRiskIC(IC = IC, risk = risk, neighbor = neighbor,
+ L2Fam = L2Fam, tol = tol)
+ })
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "asMSE",
+ neighbor = "UncondNeighborhood",
+ L2Fam = "L2ParamFamily"),
+ function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ rad <- neighbor at radius
+ if(rad == Inf) return(Inf)
+
+ trCov <- getRiskIC(IC = IC, risk = trAsCov(), L2Fam = L2Fam)
+ Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor, L2Fam = L2Fam,
+ biastype = biastype(risk))
+
+ prec <- checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ nghb <- paste(neighbor at type, "with radius", neighbor at radius)
+
+ return(list(asMSE = list(distribution = .getDistr(L2Fam),
+ neighborhood = nghb,
+ radius = neighbor at radius,
+ value = trCov$trAsCov$value + rad^2*Bias$asBias$value^2)))
+ })
+
+
+
Added: pkg/RobAStBase/R/getRiskIC_UnOvShoot.R
===================================================================
--- pkg/RobAStBase/R/getRiskIC_UnOvShoot.R (rev 0)
+++ pkg/RobAStBase/R/getRiskIC_UnOvShoot.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,275 @@
+###############################################################################
+## asymptotic under-/overshoot risk
+###############################################################################
+setMethod("getRiskIC", signature(IC = "TotalVarIC",
+ risk = "asUnOvShoot",
+ neighbor = "UncondNeighborhood",
+ L2Fam = "missing"),
+ function(IC, risk, neighbor){
+ radius <- neighbor at radius
+ L2Fam <- eval(IC at CallL2Fam)
+ L2deriv <- L2Fam at L2derivDistr[[1]]
+ if((length(L2Fam at L2derivDistr) > 1) | !is(L2deriv, "UnivariateDistribution"))
+ stop("restricted to 1-dimensional parameteric models")
+
+ bound <- risk at width*(-m1df(L2deriv, 0))
+ if(is(neighbor, "ContNeighborhood")){
+ if(radius > 2*bound)
+ stop("boundedness condition is violated!")
+ if(radius == 2*bound){
+ zi <- sign(as.vector(trafo))
+ A <- as.matrix(zi)
+ b <- zi*as.vector(trafo)*2*risk at width/radius
+ p0 <- p(L2deriv)(0)
+ if(is(L2deriv, "AbscontDistribution"))
+ ws0 <- 0
+ else
+ ws0 <- d(L2deriv)(0)
+
+ if(zi == 1)
+ a <- -b*(1-p0)/(1-ws0)
+ else
+ a <- b*(p0-ws0)/(1-ws0)
+
+ asCov <- a^2*(p0-ws0) + (zi*a+b)^2*(1-p0)
+ erg <- pnorm(-risk at width*sqrt(asCov))
+ }
+ }
+
+ if(is(neighbor, "TotalVarNeighborhood")){
+ if(radius > bound)
+ stop("boundedness condition is violated!")
+ if(radius == bound){
+ zi <- sign(as.vector(trafo))
+ A <- as.matrix(zi)
+ b <- zi*as.vector(trafo)*risk at width/radius
+ p0 <- p(L2deriv)(0)
+ if(is(L2deriv, "AbscontDistribution"))
+ ws0 <- 0
+ else
+ ws0 <- d(L2deriv)(0)
+
+ if(zi == 1)
+ a <- -b*(1-p0)/(1-ws0)
+ else
+ a <- b*(p0-ws0)/(1-ws0)
+
+ asCov <- a^2*(p0-ws0) + (zi*a+b)^2*(1-p0)
+ erg <- pnorm(-risk at width*sqrt(asCov))
+ }
+ }
+
+ stand <- as.vector(stand(IC))
+ g0 <- clipLo(IC)/abs(stand)
+ c0 <- clipUp(IC)/abs(stand) - g0
+ s <- sqrt(g0^2*p(L2deriv)(g0)
+ + (g0+c0)^2*(1 - p(L2deriv)(g0+c0))
+ + m2df(L2deriv, g0+c0) - m2df(L2deriv, g0))
+ erg <- pnorm(-risk at width*s)
+
+ nghb <- paste(neighbor at type, "with radius", neighbor at radius)
+
+ return(list(asUnOvShoot = list(distribution = .getDistr(L2Fam),
+ neighborhood = nghb, value = erg)))
+ })
+###############################################################################
+## finite-sample under-/overshoot risk
+###############################################################################
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "fiUnOvShoot",
+ neighbor = "ContNeighborhood",
+ L2Fam = "missing"),
+ function(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left"){
+ L2Fam <- eval(IC at CallL2Fam)
+ Distr <- L2Fam at distribution
+ if(!is(Distr, "Norm"))
+ stop("restricted to 1-dimensional normal location")
+
+ eps <- neighbor at radius
+ tau <- risk at width
+
+ if(!(is(IC, "ContIC") | is(IC, "TotalVarIC")))
+ stop("'IC' has to be of class 'ContIC' or 'TotalVarIC'")
+ if(is(IC, "ContIC"))
+ clip <- clip(IC)/as.vector(stand(IC))
+ if(is(IC, "TotalVarIC"))
+ clip <- clipUp(IC)/as.vector(stand(IC))
+
+ n <- sampleSize
+ m <- getdistrOption("DefaultNrFFTGridPointsExponent")
+
+ if(eps >= 1 - 1/(2*pnorm(risk at width))){
+ warning("disjointness condition is violated!")
+ erg <- 0.5
+ }else{
+ if(Algo == "B"){
+ if(cont == "left"){
+ delta1 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
+ K1 <- dbinom(0:n, size = n, prob = delta1)
+ P1 <- (1-eps)*pnorm(-clip-tau) + eps
+ p1 <- P1/delta1
+
+ summe1 <- numeric(n+1)
+ summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
+ summe1[n+1] <- (1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
+ + pbinom(q = n/2-0.1, size = n, prob = p1)))
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
+ summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
+ }
+ erg <- sum(summe1*K1)
+ }else{
+ delta2 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
+ K2 <- dbinom(0:n, size = n, prob = delta2)
+ P2 <- (1-eps)*pnorm(-clip+tau)
+ p2 <- P2/delta2
+
+ summe2 <- numeric(n+1)
+ summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
+ summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
+ + pbinom(q = n/2-0.1, size = n, prob = p2))
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
+ summe2[k+1] <- sum(P2.ste*dbinom(j, size=k, prob=p2))
+ }
+ erg <- sum(summe2*K2)
+ }
+ }else{
+ M <- 2^m
+ h <- 2*clip/M
+ x <- seq(from = -clip, to = clip, by = h)
+
+ if(cont == "right"){
+ p1 <- pnorm(x+tau)
+ p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
+ p1[1] <- p1[1] + (1-eps)*pnorm(-clip+tau)
+ p1[M] <- p1[M] + (1-eps)*pnorm(-clip-tau) + eps
+ }else{
+ p1 <- pnorm(x-tau)
+ p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
+ p1[1] <- p1[1] + (1-eps)*pnorm(-clip-tau) + eps
+ p1[M] <- p1[M] + (1-eps)*pnorm(-clip+tau)
+ }
+
+ ## FFT
+ pn <- c(p1, numeric((n-1)*M))
+
+ ## convolution theorem for DFTs
+ pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
+ pn <- (abs(pn) >= .Machine$double.eps)*pn
+ pn <- cumsum(pn)
+
+ k <- n*(M-1)/2
+ erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
+ if(cont == "right") erg <- 1 - erg
+ }
+ }
+
+ nghb <- paste(neighbor at type, "with radius", neighbor at radius)
+
+ return(list(fiUnOvShoot = list(distribution = .getDistr(eval(IC at CallL2Fam)),
+ neighborhood = nghb, value = erg)))
+ })
+setMethod("getRiskIC", signature(IC = "IC",
+ risk = "fiUnOvShoot",
+ neighbor = "TotalVarNeighborhood",
+ L2Fam = "missing"),
+ function(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left"){
+ L2Fam <- eval(IC at CallL2Fam)
+ Distr <- L2Fam at distribution
+ if(!is(Distr, "Norm"))
+ stop("restricted to 1-dimensional normal location")
+
+ delta <- neighbor at radius
+ tau <- risk at width
+
+ if(!(is(IC, "ContIC") | is(IC, "TotalVarIC")))
+ stop("'IC' has to be of class 'ContIC' or 'TotalVarIC'")
+ if(is(IC, "ContIC"))
+ clip <- clip(IC)/as.vector(stand(IC))
+ if(is(IC, "TotalVarIC"))
+ clip <- clipUp(IC)/as.vector(stand(IC))
+
+ n <- sampleSize
+ m <- getdistrOption("DefaultNrFFTGridPointsExponent")
+
+ if(delta >= pnorm(risk at width) - 0.5){
+ warning("disjointness condition is violated!")
+ erg <- 0.5
+ }else{
+ if(Algo == "B"){
+ if(cont == "left"){
+ delta1 <- min(pnorm(-clip-tau)+delta, 1) + 1 - min(pnorm(clip-tau)+delta, 1)
+ K1 <- dbinom(0:n, size = n, prob = delta1)
+ P1 <- min(pnorm(-clip-tau) + delta, 1)
+ p1 <- min(P1/delta1, 1)
+
+ summe1 <- numeric(n+1)
+ summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
+ summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
+ }
+ summe1[n+1] <- 1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
+ + pbinom(q = n/2-0.1, size = n, prob = p1))
+ erg <- sum(summe1*K1)
+ }else{
+ delta2 <- max(0, pnorm(-clip+tau)-delta) + 1 - max(0, pnorm(clip+tau)-delta)
+ K2 <- dbinom(0:n, size = n, prob = delta2)
+ P2 <- max(0, pnorm(-clip+tau) - delta)
+ p2 <- P2/delta2
+
+ summe2 <- numeric(n+1)
+ summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
+ summe2[k+1] <- sum(P2.ste*dbinom(j, size = k, prob = p2))
+ }
+ summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
+ + pbinom(q = n/2-0.1, size = n, prob = p2))
+ erg <- sum(summe2*K2)
+ }
+ }else{
+ M <- 2^m
+ h <- 2*clip/M
+ x <- seq(from = -clip, to = clip, by = h)
+
+ if(cont == "right"){
+ p1 <- pnorm(x+tau)
+ p1 <- p1[2:(M + 1)] - p1[1:M]
+ p1[1] <- p1[1] + pnorm(-clip+tau) - delta
+ p1[M] <- p1[M] + pnorm(-clip-tau) + delta
+ }else{
+ p1 <- pnorm(x-tau)
+ p1 <- p1[2:(M + 1)] - p1[1:M]
+ p1[1] <- p1[1] + pnorm(-clip-tau) + delta
+ p1[M] <- p1[M] + pnorm(-clip+tau) - delta
+ }
+
+ ## FFT
+ pn <- c(p1, numeric((n-1)*M))
+
+ ## convolution theorem for DFTs
+ pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
+ pn <- (abs(pn) >= .Machine$double.eps)*pn
+ pn <- cumsum(pn)
+
+ k <- n*(M-1)/2
+ erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
+ if(cont == "right") erg <- 1-erg
+ }
+ }
+
+ nghb <- paste(neighbor at type, "with radius", neighbor at radius)
+
+ return(list(fiUnOvShoot = list(distribution = .getDistr(eval(IC at CallL2Fam)),
+ neighborhood = nghb, value = erg)))
+ })
Added: pkg/RobAStBase/R/utils.R
===================================================================
--- pkg/RobAStBase/R/utils.R (rev 0)
+++ pkg/RobAStBase/R/utils.R 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,16 @@
+.eq <-function(x,y = 0*x, tol = 1e-7) abs(x-y)<tol
+
+.getDistr <- function(L2Fam){
+ slots <- slotNames(L2Fam at distribution@param)
+ slots <- slots[slots != "name"]
+ nrvalues <- length(slots)
+ if (nrvalues > 0) {
+ values = numeric(nrvalues)
+ for (i in 1:nrvalues)
+ values[i] <- attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
+
+ paramstring <- paste("(", paste(values, collapse = ", "), ")", sep = "")
+ }
+ distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
+}
+
Modified: pkg/RobAStBase/chm/00Index.html
===================================================================
--- pkg/RobAStBase/chm/00Index.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/00Index.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -50,8 +50,8 @@
<table width="100%">
<tr><td width="25%"><a href="BdStWeight-class.html">BdStWeight-class</a></td>
<td>Robust Weight classes for bounded, standardized weights</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">biastype,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">biastype,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
<tr><td width="25%"><a href="BoundedWeight-class.html">BoundedWeight-class</a></td>
<td>Robust Weight classes for bounded weights</td></tr>
</table>
@@ -169,6 +169,38 @@
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
<tr><td width="25%"><a href="generateICfct.html">generateIC.fct-methods</a></td>
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,UncondNeighborhood-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC-methods</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC-methods</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
<tr><td width="25%"><a href="getweight.html">getweight</a></td>
<td>Generating weights</td></tr>
<tr><td width="25%"><a href="getweight.html">getweight,BdStWeight,TotalVarNeighborhood,BiasType-method</a></td>
@@ -188,6 +220,8 @@
<table width="100%">
<tr><td width="25%"><a href="HampelWeight-class.html">HampelWeight-class</a></td>
<td>Robust Weight classes for weights of Hampel type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">HampIC-class</a></td>
+<td>Influence curve of Hampel type</td></tr>
</table>
<h2><a name="I">-- I --</a></h2>
@@ -226,12 +260,10 @@
<td>Generic function for the computation of location M estimators</td></tr>
<tr><td width="25%"><a href="locMEstimator.html">locMEstimator-methods</a></td>
<td>Generic function for the computation of location M estimators</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">lowerCase</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">lowerCase,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">lowerCase</a></td>
+<td>Influence curve of Hampel type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">lowerCase,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
<tr><td width="25%"><a href="ContIC-class.html">lowerCase<-,ContIC-method</a></td>
<td>Influence curve of contamination type</td></tr>
<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase<-,TotalVarIC-method</a></td>
@@ -241,13 +273,13 @@
<h2><a name="M">-- M --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="makeIC.html">makeIC</a></td>
+<tr><td width="25%"><a href="makeIC-methods.html">makeIC</a></td>
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
-<tr><td width="25%"><a href="makeIC.html">makeIC,IC,L2ParamFamily-method</a></td>
+<tr><td width="25%"><a href="makeIC-methods.html">makeIC,IC,L2ParamFamily-method</a></td>
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
-<tr><td width="25%"><a href="makeIC.html">makeIC,IC,missing-method</a></td>
+<tr><td width="25%"><a href="makeIC-methods.html">makeIC,IC,missing-method</a></td>
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
-<tr><td width="25%"><a href="makeIC.html">makeIC-methods</a></td>
+<tr><td width="25%"><a href="makeIC-methods.html">makeIC-methods</a></td>
<td>Generic Function for making ICs consistent at a possibly different model</td></tr>
<tr><td width="25%"><a href="InfluenceCurve-class.html">Map,InfluenceCurve-method</a></td>
<td>Influence curve</td></tr>
@@ -294,18 +326,14 @@
<td>Robust model</td></tr>
<tr><td width="25%"><a href="Neighborhood-class.html">Neighborhood-class</a></td>
<td>Neighborhood</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">normtype,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">neighborRadius</a></td>
+<td>Influence curve of Hampel type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">neighborRadius,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">neighborRadius<-,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">normtype,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
</table>
<h2><a name="O">-- O --</a></h2>
@@ -378,14 +406,12 @@
<td>Neighborhood</td></tr>
<tr><td width="25%"><a href="TotalVarIC-class.html">show,TotalVarIC-method</a></td>
<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">stand</a></td>
-<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">stand</a></td>
+<td>Influence curve of Hampel type</td></tr>
<tr><td width="25%"><a href="BdStWeight-class.html">stand,BdStWeight-method</a></td>
<td>Robust Weight classes for bounded, standardized weights</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">stand,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">stand,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">stand,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
<tr><td width="25%"><a href="BdStWeight-class.html">stand<-,BdStWeight-method</a></td>
<td>Robust Weight classes for bounded, standardized weights</td></tr>
<tr><td width="25%"><a href="ContIC-class.html">stand<-,ContIC-method</a></td>
@@ -421,13 +447,13 @@
<table width="100%">
<tr><td width="25%"><a href="RobWeight-class.html">weight</a></td>
<td>Robust Weight classes</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">weight,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="HampIC-class.html">weight,HampIC-method</a></td>
+<td>Influence curve of Hampel type</td></tr>
<tr><td width="25%"><a href="RobWeight-class.html">weight,RobWeight-method</a></td>
<td>Robust Weight classes</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">weight,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
<tr><td width="25%"><a href="RobWeight-class.html">weight<-,RobWeight-method</a></td>
<td>Robust Weight classes</td></tr>
+<tr><td width="25%"><a href="RobWeight-class.html">weight<--methods</a></td>
+<td>Robust Weight classes</td></tr>
</table>
</body></html>
Modified: pkg/RobAStBase/chm/ContIC-class.html
===================================================================
--- pkg/RobAStBase/chm/ContIC-class.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/ContIC-class.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -15,21 +15,10 @@
<param name="keyword" value="R: clip,ContIC-method">
<param name="keyword" value="R: clip<-">
<param name="keyword" value="R: clip<-,ContIC-method">
-<param name="keyword" value="R: lowerCase">
-<param name="keyword" value="R: lowerCase,ContIC-method">
<param name="keyword" value="R: lowerCase<-">
<param name="keyword" value="R: lowerCase<-,ContIC-method">
-<param name="keyword" value="R: neighborRadius">
-<param name="keyword" value="R: neighborRadius,ContIC-method">
-<param name="keyword" value="R: neighborRadius<-">
-<param name="keyword" value="R: neighborRadius<-,ContIC-method">
-<param name="keyword" value="R: stand">
-<param name="keyword" value="R: stand,ContIC-method">
<param name="keyword" value="R: stand<-">
<param name="keyword" value="R: stand<-,ContIC-method">
-<param name="keyword" value="R: weight,ContIC-method">
-<param name="keyword" value="R: biastype,ContIC-method">
-<param name="keyword" value="R: normtype,ContIC-method">
<param name="keyword" value="R: generateIC,ContNeighborhood,L2ParamFamily-method">
<param name="keyword" value="R: show,ContIC-method">
<param name="keyword" value=" Influence curve of contamination type">
@@ -116,7 +105,8 @@
<h3>Extends</h3>
<p>
-Class <code>"IC"</code>, directly.<br>
+Class <code>"HampIC"</code>, directly.<br>
+Class <code>"IC"</code>, by class <code>"HampIC"</code>.<br>
Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
</p>
@@ -144,36 +134,14 @@
replacement function for slot <code>clip</code>. </dd>
-<dt>stand</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>stand</code>. </dd>
-
-
<dt>stand<-</dt><dd><code>signature(object = "ContIC")</code>:
replacement function for slot <code>stand</code>. </dd>
-<dt>weight</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>weight</code>. </dd>
-<dt>biastype</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>biastype</code>. </dd>
-<dt>normtype</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>normtype</code>. </dd>
-<dt>lowerCase</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>lowerCase</code>. </dd>
-
-
<dt>lowerCase<-</dt><dd><code>signature(object = "ContIC")</code>:
replacement function for slot <code>lowerCase</code>. </dd>
-<dt>neighborRadius</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>neighborRadius<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>neighborRadius</code>. </dd>
-
-
<dt>generateIC</dt><dd><code>signature(neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily")</code>:
generate an object of class <code>"ContIC"</code>. Rarely called directly. </dd>
@@ -202,7 +170,7 @@
<h3>See Also</h3>
<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code> <code><a href="HampIC-class.html">HampIC-class</a></code>
</p>
Modified: pkg/RobAStBase/chm/ContIC.html
===================================================================
--- pkg/RobAStBase/chm/ContIC.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/ContIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -113,7 +113,7 @@
<h3>See Also</h3>
<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code> , <code><a href="HampIC-class.html">HampIC-class</a></code>
</p>
Added: pkg/RobAStBase/chm/HampIC-class.html
===================================================================
--- pkg/RobAStBase/chm/HampIC-class.html (rev 0)
+++ pkg/RobAStBase/chm/HampIC-class.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,172 @@
+<html><head><title>Influence curve of Hampel type</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>HampIC-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: HampIC-class">
+<param name="keyword" value="R: lowerCase">
+<param name="keyword" value="R: lowerCase,HampIC-method">
+<param name="keyword" value="R: neighborRadius">
+<param name="keyword" value="R: neighborRadius,HampIC-method">
+<param name="keyword" value="R: neighborRadius<-">
+<param name="keyword" value="R: neighborRadius<-,HampIC-method">
+<param name="keyword" value="R: stand">
+<param name="keyword" value="R: stand,HampIC-method">
+<param name="keyword" value="R: weight,HampIC-method">
+<param name="keyword" value="R: biastype,HampIC-method">
+<param name="keyword" value="R: normtype,HampIC-method">
+<param name="keyword" value=" Influence curve of Hampel type">
+</object>
+
+
+<h2>Influence curve of Hampel type</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (partial) influence curves of Hampel (= total variation or contamination) type;
+used as common mother class for classes <code>ContIC</code> and <code>TotalVarIC</code>.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("HampIC", ...)</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>CallL2Fam</code>:</dt><dd>object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </dd>
+
+
+<dt><code>name</code>:</dt><dd>object of class <code>"character"</code> </dd>
+
+
+<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code></dd>
+
+
+<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </dd>
+
+
+<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
+with two columns named <code>method</code> and <code>message</code>:
+additional informations. </dd>
+
+
+<dt><code>stand</code>:</dt><dd>object of class <code>"matrix"</code>:
+standardizing matrix. </dd>
+
+
+<dt><code>weight</code>:</dt><dd>object of class <code>"RobWeight"</code>:
+weight function </dd>
+
+
+<dt><code>biastype</code>:</dt><dd>object of class <code>"BiasType"</code>:
+bias type (symmetric/onsided/asymmetric) </dd>
+<dt><code>normtype</code>:</dt><dd>object of class <code>"NormType"</code>:
+norm type (Euclidean, information/self-standardized)</dd>
+
+
+<dt><code>lowerCase</code>:</dt><dd>object of class <code>"OptionalNumeric"</code>:
+optional constant for lower case solution. </dd>
+
+
+<dt><code>neighborRadius</code>:</dt><dd>object of class <code>"numeric"</code>:
+radius of the corresponding (unconditional) contamination
+neighborhood. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"IC"</code>, directly.<br>
+Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+</p>
+
+<dt>stand</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>stand</code>. </dd>
+
+
+<dt>weight</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>weight</code>. </dd>
+
+
+<dt>biastype</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>biastype</code>. </dd>
+<dt>normtype</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>normtype</code>. </dd>
+<dt>lowerCase</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>lowerCase</code>. </dd>
+
+
+<dt>neighborRadius</dt><dd><code>signature(object = "HampIC")</code>:
+accessor function for slot <code>neighborRadius</code>. </dd>
+
+
+<dt>neighborRadius<-</dt><dd><code>signature(object = "HampIC")</code>:
+replacement function for slot <code>neighborRadius</code>. </dd>
+
+<p>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter Ruckdeschel at uni-bayreuth.de">Peter Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Hampributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("HampIC")
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/RobAStBase/chm/RobAStBase.chm
===================================================================
(Binary files differ)
Modified: pkg/RobAStBase/chm/RobAStBase.hhp
===================================================================
--- pkg/RobAStBase/chm/RobAStBase.hhp 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/RobAStBase.hhp 2008-03-28 02:21:40 UTC (rev 80)
@@ -20,6 +20,7 @@
ContNeighborhood.html
FixRobModel-class.html
FixRobModel.html
+HampIC-class.html
HampelWeight-class.html
IC-class.html
IC.html
@@ -40,9 +41,12 @@
evalIC.html
generateIC.html
generateICfct.html
+getBiasIC.html
+getRiskIC.html
getweight.html
infoPlot.html
+internals.html
locMEstimator.html
-makeIC.html
+makeIC-methods.html
oneStepEstimator.html
optIC.html
Modified: pkg/RobAStBase/chm/RobAStBase.toc
===================================================================
--- pkg/RobAStBase/chm/RobAStBase.toc 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/RobAStBase.toc 2008-03-28 02:21:40 UTC (rev 80)
@@ -10,6 +10,14 @@
</OBJECT>
<UL>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value=".eq">
+<param name="Local" value="internals.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value=".getDistr">
+<param name="Local" value="internals.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="addInfo<-">
<param name="Local" value="InfluenceCurve-class.html">
</OBJECT>
@@ -30,8 +38,8 @@
<param name="Local" value="BdStWeight-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="biastype,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="biastype,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="BoundedWeight-class">
@@ -242,6 +250,70 @@
<param name="Local" value="generateICfct.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getBiasIC">
+<param name="Local" value="getBiasIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getBiasIC,IC,UncondNeighborhood-method">
+<param name="Local" value="getBiasIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getBiasIC-methods">
+<param name="Local" value="getBiasIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asBias,UncondNeighborhood,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asCov,missing,L2ParamFamily-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asCov,missing,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,asMSE,UncondNeighborhood,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,trAsCov,missing,L2ParamFamily-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,IC,trAsCov,missing,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="getRiskIC-methods">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="getweight">
<param name="Local" value="getweight.html">
</OBJECT>
@@ -270,6 +342,10 @@
<param name="Local" value="HampelWeight-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="HampIC-class">
+<param name="Local" value="HampIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="IC">
<param name="Local" value="IC.html">
</OBJECT>
@@ -318,6 +394,10 @@
<param name="Local" value="InfRobModel-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="internals_for_RobAStBase">
+<param name="Local" value="internals.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="locMEstimator">
<param name="Local" value="locMEstimator.html">
</OBJECT>
@@ -331,17 +411,13 @@
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="lowerCase">
-<param name="Local" value="ContIC-class.html">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="lowerCase,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="lowerCase,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="lowerCase,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="lowerCase<-">
<param name="Local" value="ContIC-class.html">
</OBJECT>
@@ -355,19 +431,19 @@
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="makeIC">
-<param name="Local" value="makeIC.html">
+<param name="Local" value="makeIC-methods.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="makeIC,IC,L2ParamFamily-method">
-<param name="Local" value="makeIC.html">
+<param name="Local" value="makeIC-methods.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="makeIC,IC,missing-method">
-<param name="Local" value="makeIC.html">
+<param name="Local" value="makeIC-methods.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="makeIC-methods">
-<param name="Local" value="makeIC.html">
+<param name="Local" value="makeIC-methods.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Map,InfluenceCurve-method">
@@ -455,33 +531,25 @@
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="neighborRadius">
-<param name="Local" value="ContIC-class.html">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="neighborRadius,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="neighborRadius,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="neighborRadius,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="neighborRadius<-">
-<param name="Local" value="ContIC-class.html">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="neighborRadius<-,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="neighborRadius<-,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="neighborRadius<-,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
+<param name="Name" value="normtype,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="normtype,ContIC-method">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="oneStepEstimator">
<param name="Local" value="oneStepEstimator.html">
</OBJECT>
@@ -591,21 +659,17 @@
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="stand">
-<param name="Local" value="ContIC-class.html">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="stand,BdStWeight-method">
<param name="Local" value="BdStWeight-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="stand,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="stand<-">
<param name="Local" value="ContIC-class.html">
</OBJECT>
@@ -650,18 +714,14 @@
<param name="Local" value="RobWeight-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="weight,ContIC-method">
-<param name="Local" value="ContIC-class.html">
+<param name="Name" value="weight,HampIC-method">
+<param name="Local" value="HampIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="weight,RobWeight-method">
<param name="Local" value="RobWeight-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="weight,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="weight<-">
<param name="Local" value="RobWeight-class.html">
</OBJECT>
@@ -669,6 +729,10 @@
<param name="Name" value="weight<-,RobWeight-method">
<param name="Local" value="RobWeight-class.html">
</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="weight<--methods">
+<param name="Local" value="RobWeight-class.html">
+</OBJECT>
</UL>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Package RobAStBase: Titles">
@@ -728,9 +792,13 @@
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic Function for making ICs consistent at a possibly different model">
-<param name="Local" value="makeIC.html">
+<param name="Local" value="makeIC-methods.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for the computation of a risk for an IC">
+<param name="Local" value="getRiskIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of location M estimators">
<param name="Local" value="locMEstimator.html">
</OBJECT>
@@ -743,6 +811,10 @@
<param name="Local" value="optIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for the computation of the asymptotic bias for an IC">
+<param name="Local" value="getBiasIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the generation of influence curves">
<param name="Local" value="generateIC.html">
</OBJECT>
@@ -755,10 +827,18 @@
<param name="Local" value="ContIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Influence curve of Hampel type">
+<param name="Local" value="HampIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Influence curve of total variation type">
<param name="Local" value="TotalVarIC-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Internal / Helper functions of package RobAStBase">
+<param name="Local" value="internals.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Neighborhood">
<param name="Local" value="Neighborhood-class.html">
</OBJECT>
Modified: pkg/RobAStBase/chm/RobWeight-class.html
===================================================================
--- pkg/RobAStBase/chm/RobWeight-class.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/RobWeight-class.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -7,11 +7,12 @@
<table width="100%"><tr><td>RobWeight-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: RobWeight-class">
<param name="keyword" value="R: name,RobWeight-method">
-<param name="keyword" value="R: weight,RobWeight-method">
<param name="keyword" value="R: name<-,RobWeight-method">
+<param name="keyword" value="R: weight,RobWeight-method">
+<param name="keyword" value="R: weight">
+<param name="keyword" value="R: weight<--methods">
<param name="keyword" value="R: weight<-,RobWeight-method">
<param name="keyword" value="R: weight<-">
-<param name="keyword" value="R: weight">
<param name="keyword" value=" Robust Weight classes">
</object>
@@ -52,13 +53,11 @@
<dt>weight</dt><dd><code>signature(object = "RobWeight")</code>:
-accessor function for slot <code>name</code>. </dd>
+accessor function for slot <code>weight</code>. </dd>
-<dt>weight<-</dt><dd><code>signature(object = "RobWeight", value = "function")</code>:
+<dt>weight<-</dt><dd><code>signature(object = "RobWeight", value = "ANY")</code>:
replacement function for slot <code>weight</code>. </dd>
-
-<p>
</dl>
<h3>Author(s)</h3>
Modified: pkg/RobAStBase/chm/TotalVarIC-class.html
===================================================================
--- pkg/RobAStBase/chm/TotalVarIC-class.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/TotalVarIC-class.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -15,14 +15,9 @@
<param name="keyword" value="R: clipUp,TotalVarIC-method">
<param name="keyword" value="R: clipUp<-">
<param name="keyword" value="R: clipUp<-,TotalVarIC-method">
-<param name="keyword" value="R: lowerCase,TotalVarIC-method">
<param name="keyword" value="R: lowerCase<-,TotalVarIC-method">
-<param name="keyword" value="R: neighborRadius,TotalVarIC-method">
-<param name="keyword" value="R: neighborRadius<-,TotalVarIC-method">
<param name="keyword" value="R: show,TotalVarIC-method">
-<param name="keyword" value="R: stand,TotalVarIC-method">
<param name="keyword" value="R: stand<-,TotalVarIC-method">
-<param name="keyword" value="R: weight,TotalVarIC-method">
<param name="keyword" value="R: generateIC,TotalVarNeighborhood,L2ParamFamily-method">
<param name="keyword" value=" Influence curve of total variation type">
</object>
@@ -100,7 +95,8 @@
<h3>Extends</h3>
<p>
-Class <code>"IC"</code>, directly.<br>
+Class <code>"HampIC"</code>, directly.<br>
+Class <code>"IC"</code>, by class <code>"HampIC"</code>.<br>
Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
</p>
@@ -128,26 +124,10 @@
replacement function for slot <code>clipUp</code>. </dd>
-<dt>stand</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>stand</code>. </dd>
-
-
<dt>stand<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
replacement function for slot <code>stand</code>. </dd>
-<dt>weight</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>weight</code>. </dd>
-
-
-<dt>neighborRadius</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>neighborRadius<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>neighborRadius</code>. </dd>
-
-
<dt>generateIC</dt><dd><code>signature(neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily")</code>:
generate an object of class <code>"TotalVarIC"</code>. Rarely called directly. </dd>
@@ -176,7 +156,7 @@
<h3>See Also</h3>
<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>, <code><a href="HampIC-class.html">HampIC-class</a></code>
</p>
Added: pkg/RobAStBase/chm/getBiasIC.html
===================================================================
--- pkg/RobAStBase/chm/getBiasIC.html (rev 0)
+++ pkg/RobAStBase/chm/getBiasIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,138 @@
+<html><head><title>Generic function for the computation of the asymptotic bias for an IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getBiasIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getBiasIC">
+<param name="keyword" value="R: getBiasIC-methods">
+<param name="keyword" value="R: getBiasIC,IC,UncondNeighborhood-method">
+<param name="keyword" value=" Generic function for the computation of the asymptotic bias for an IC">
+</object>
+
+
+<h2>Generic function for the computation of the asymptotic bias for an IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the asymptotic bias for an IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getBiasIC(IC, neighbor, ...)
+
+## S4 method for signature 'IC, UncondNeighborhood':
+getBiasIC(IC, neighbor, L2Fam, biastype = symmetricBias(),
+ normtype = NormType(), tol = .Machine$double.eps^0.25)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code></td></tr>
+<tr valign="top"><td><code>normtype</code></td>
+<td>
+object of class <code>"NormType"</code></td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+</table>
+
+<h3>Details</h3>
+
+
+
+
+<h3>Value</h3>
+
+<p>
+The bias of the IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>IC = "IC", neighbor = "UncondNeighborhood"</dt><dd>determines the as. bias by random evaluation of the IC;
+this random evaluation is done by the internal S4-method
+<code>.evalBiasIC</code>; this latter dispatches according to
+the signature <code>IC, neighbor, biastype</code>.<br>
+For signature <code>IC="IC", neighbor = "ContNeighborhood",
+ biastype = "BiasType"</code>, also an argument <code>normtype</code>
+is used to be able to use self- or information standardizing
+norms; besides this the signatures
+<code>IC="IC", neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"</code>,
+<code>IC="IC", neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"</code>, and
+<code>IC="IC", neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"</code> are implemented.
+</dd>
+</dl>
+
+<h3>Note</h3>
+
+<p>
+This generic function is still under construction.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Bias
+of M-estimators on Neighborhoods.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a href="InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/getRiskIC.html
===================================================================
--- pkg/RobAStBase/chm/getRiskIC.html (rev 0)
+++ pkg/RobAStBase/chm/getRiskIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,229 @@
+<html><head><title>Generic function for the computation of a risk for an IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getRiskIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getRiskIC">
+<param name="keyword" value="R: getRiskIC-methods">
+<param name="keyword" value="R: getRiskIC,IC,asCov,missing,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,asCov,missing,L2ParamFamily-method">
+<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,L2ParamFamily-method">
+<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method">
+<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method">
+<param name="keyword" value="R: getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method">
+<param name="keyword" value=" Generic function for the computation of a risk for an IC">
+</object>
+
+
+<h2>Generic function for the computation of a risk for an IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of a risk for an IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getRiskIC(IC, risk, neighbor, L2Fam, ...)
+
+## S4 method for signature 'IC, asCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'TotalVarIC, asUnOvShoot,
+## UncondNeighborhood, missing':
+getRiskIC(IC, risk, neighbor)
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## ContNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## TotalVarNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of <code>IC</code>
+using <code>checkIC</code>.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The risk of an IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations; uses method <code><a href="getBiasIC.html">getBiasIC</a></code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations and <code>L2Fam</code>; uses method <code><a href="getBiasIC.html">getBiasIC</a></code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> in case of total variation neighborhoods; uses method <code><a href="getBiasIC.html">getBiasIC</a></code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code> in case of total variation
+neighborhoods; uses method <code><a href="getBiasIC.html">getBiasIC</a></code>. </dd>
+
+
+<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic mean square error of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic mean square error of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic under-/overshoot risk of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
+</dl>
+
+<h3>Note</h3>
+
+<p>
+This generic function is still under construction.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a><br>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+of M-estimators on Neighborhoods.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'getRiskIC-methods.html')" style="text-decoration: underline; color: blue; cursor: hand">getRiskIC-methods</a></code>, <code><a href="InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/RobAStBase/chm/getweight.html
===================================================================
--- pkg/RobAStBase/chm/getweight.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/getweight.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -42,6 +42,18 @@
## S4 method for signature 'HampelWeight, ContNeighborhood,
## BiasType':
minbiasweight(Weight, neighbor, biastype, normtype)
+## S4 method for signature 'HampelWeight, ContNeighborhood,
+## onesidedBias':
+getweight(Weight, neighbor, biastype, ...)
+## S4 method for signature 'HampelWeight, ContNeighborhood,
+## onesidedBias':
+minbiasweight(Weight, neighbor, biastype,...)
+## S4 method for signature 'HampelWeight, ContNeighborhood,
+## asymmetricBias':
+getweight(Weight, neighbor, biastype, ...)
+## S4 method for signature 'HampelWeight, ContNeighborhood,
+## asymmetricBias':
+minbiasweight(Weight, neighbor, biastype,...)
</pre>
@@ -63,6 +75,9 @@
<tr valign="top"><td><code>normtype</code></td>
<td>
Object of class <code>"NormType"</code> — only for signature <code>HampelWeight,ContNeighborhood,BiasType</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+possibly additional (unused) arguments — like in a call to the less specific methods.</td></tr>
</table>
<h3>Details</h3>
Added: pkg/RobAStBase/chm/internals.html
===================================================================
--- pkg/RobAStBase/chm/internals.html (rev 0)
+++ pkg/RobAStBase/chm/internals.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,81 @@
+<html><head><title>Internal / Helper functions of package RobAStBase</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>internals_for_RobAStBase(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: internals_for_RobAStBase">
+<param name="keyword" value="R: .eq">
+<param name="keyword" value="R: .getDistr">
+<param name="keyword" value=" Internal / Helper functions of package RobAStBase">
+</object>
+
+
+<h2>Internal / Helper functions of package RobAStBase</h2>
+
+
+<h3>Description</h3>
+
+<p>
+These functions are used internally by package RobAStBase.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+.eq(x,y = 0*x, tol = 1e-7)
+.getDistr(L2Fam)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+a (numeric) vector</td></tr>
+<tr valign="top"><td><code>y</code></td>
+<td>
+a (numeric) vector</td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+numeric — tolerance</td></tr>
+<tr valign="top"><td><code>L2fam</code></td>
+<td>
+object of class <code>L2ParamFamily</code></td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+<code>.eq</code>checks equality of two vectors up to a given precision;
+<code>.getDistr</code> produces a string with the class of the family and its parameter value;
+</p>
+
+
+<h3>Value</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>.eq</code></td>
+<td>
+</td></tr>
+<tr valign="top"><td><code>.getDistr</code></td>
+<td>
+</td></tr>
+</table>
+<p>
+ <code>character</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/makeIC-methods.html
===================================================================
--- pkg/RobAStBase/chm/makeIC-methods.html (rev 0)
+++ pkg/RobAStBase/chm/makeIC-methods.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,105 @@
+<html><head><title>Generic Function for making ICs consistent at a possibly different model</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>makeIC-methods(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: makeIC">
+<param name="keyword" value="R: makeIC-methods">
+<param name="keyword" value="R: makeIC,IC,missing-method">
+<param name="keyword" value="R: makeIC,IC,L2ParamFamily-method">
+<param name="keyword" value=" Generic Function for making ICs consistent at a possibly different model">
+</object>
+
+
+<h2>Generic Function for making ICs consistent at a possibly different model</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for providing centering and Fisher consistency of ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+makeIC(IC, L2Fam, ...)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"IC"</code> </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures; may be missing. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+An IC at the model.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>makeIC</dt><dd><code>signature(IC = "IC", L2Fam = "missing"</code>: ...</dd>
+<dt>makeIC</dt><dd><code>signature(IC = "IC", L2Fam = "L2ParamFamily"</code>: ...</dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'L2ParamFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("IC")
+B <- BinomFamily(13, 0.3)
+makeIC(IC1,B)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Deleted: pkg/RobAStBase/chm/makeIC.html
===================================================================
--- pkg/RobAStBase/chm/makeIC.html 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/chm/makeIC.html 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,105 +0,0 @@
-<html><head><title>Generic Function for making ICs consistent at a possibly different model</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>makeIC-methods(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: makeIC">
-<param name="keyword" value="R: makeIC-methods">
-<param name="keyword" value="R: makeIC,IC,missing-method">
-<param name="keyword" value="R: makeIC,IC,L2ParamFamily-method">
-<param name="keyword" value=" Generic Function for making ICs consistent at a possibly different model">
-</object>
-
-
-<h2>Generic Function for making ICs consistent at a possibly different model</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for providing centering and Fisher consistency of ICs.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-makeIC(IC, L2Fam, ...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>IC</code></td>
-<td>
-object of class <code>"IC"</code> </td></tr>
-<tr valign="top"><td><code>L2Fam</code></td>
-<td>
-L2-differentiable family of probability measures; may be missing. </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-An IC at the model.</p>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>makeIC</dt><dd><code>signature(IC = "IC", L2Fam = "missing"</code>: ...</dd>
-<dt>makeIC</dt><dd><code>signature(IC = "IC", L2Fam = "L2ParamFamily"</code>: ...</dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('distrMod', 'L2ParamFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- new("IC")
-B <- BinomFamily(13, 0.3)
-makeIC(IC1,B)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/RobAStBase/man/ContIC-class.Rd
===================================================================
--- pkg/RobAStBase/man/ContIC-class.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/ContIC-class.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -10,21 +10,10 @@
\alias{clip,ContIC-method}
\alias{clip<-}
\alias{clip<-,ContIC-method}
-\alias{lowerCase}
-\alias{lowerCase,ContIC-method}
\alias{lowerCase<-}
\alias{lowerCase<-,ContIC-method}
-\alias{neighborRadius}
-\alias{neighborRadius,ContIC-method}
-\alias{neighborRadius<-}
-\alias{neighborRadius<-,ContIC-method}
-\alias{stand}
-\alias{stand,ContIC-method}
\alias{stand<-}
\alias{stand<-,ContIC-method}
-\alias{weight,ContIC-method}
-\alias{biastype,ContIC-method}
-\alias{normtype,ContIC-method}
\alias{generateIC,ContNeighborhood,L2ParamFamily-method}
\alias{show,ContIC-method}
@@ -84,7 +73,8 @@
}
}
\section{Extends}{
-Class \code{"IC"}, directly.\cr
+Class \code{"HampIC"}, directly.\cr
+Class \code{"IC"}, by class \code{"HampIC"}.\cr
Class \code{"InfluenceCurve"}, by class \code{"IC"}.
}
\section{Methods}{
@@ -104,30 +94,12 @@
\item{clip<-}{\code{signature(object = "ContIC")}:
replacement function for slot \code{clip}. }
- \item{stand}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{stand}. }
-
\item{stand<-}{\code{signature(object = "ContIC")}:
replacement function for slot \code{stand}. }
- \item{weight}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{weight}. }
- \item{biastype}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{biastype}. }
- \item{normtype}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{normtype}. }
- \item{lowerCase}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{lowerCase}. }
-
\item{lowerCase<-}{\code{signature(object = "ContIC")}:
replacement function for slot \code{lowerCase}. }
- \item{neighborRadius}{\code{signature(object = "ContIC")}:
- accessor function for slot \code{neighborRadius}. }
-
- \item{neighborRadius<-}{\code{signature(object = "ContIC")}:
- replacement function for slot \code{neighborRadius}. }
-
\item{generateIC}{\code{signature(neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily")}:
generate an object of class \code{"ContIC"}. Rarely called directly. }
@@ -142,7 +114,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{IC-class}}, \code{\link{ContIC}}}
+\seealso{\code{\link{IC-class}}, \code{\link{ContIC}} \code{\link{HampIC-class}}}
\examples{
IC1 <- new("ContIC")
plot(IC1)
Modified: pkg/RobAStBase/man/ContIC.Rd
===================================================================
--- pkg/RobAStBase/man/ContIC.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/ContIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -49,7 +49,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{IC-class}}, \code{\link{ContIC}}}
+\seealso{\code{\link{IC-class}}, \code{\link{ContIC}} , \code{\link{HampIC-class}}}
\examples{
IC1 <- ContIC()
plot(IC1)
Added: pkg/RobAStBase/man/HampIC-class.Rd
===================================================================
--- pkg/RobAStBase/man/HampIC-class.Rd (rev 0)
+++ pkg/RobAStBase/man/HampIC-class.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,101 @@
+\name{HampIC-class}
+\docType{class}
+\alias{HampIC-class}
+\alias{lowerCase}
+\alias{lowerCase,HampIC-method}
+\alias{neighborRadius}
+\alias{neighborRadius,HampIC-method}
+\alias{neighborRadius<-}
+\alias{neighborRadius<-,HampIC-method}
+\alias{stand}
+\alias{stand,HampIC-method}
+\alias{weight,HampIC-method}
+\alias{biastype,HampIC-method}
+\alias{normtype,HampIC-method}
+
+\title{Influence curve of Hampel type}
+\description{Class of (partial) influence curves of Hampel (= total variation or contamination) type;
+used as common mother class for classes \code{ContIC} and \code{TotalVarIC}.
+}
+\section{Objects from the Class}{
+ Objects can be created by calls of the form \code{new("HampIC", ...)}.
+}
+\section{Slots}{
+ \describe{
+ \item{\code{CallL2Fam}:}{ object of class \code{"call"}:
+ creates an object of the underlying L2-differentiable
+ parametric family. }
+
+ \item{\code{name}:}{ object of class \code{"character"} }
+
+ \item{\code{Curve}:}{ object of class \code{"EuclRandVarList"}}
+
+ \item{\code{Risks}:}{ object of class \code{"list"}:
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
+
+ \item{\code{Infos}:}{ object of class \code{"matrix"}
+ with two columns named \code{method} and \code{message}:
+ additional informations. }
+
+ \item{\code{stand}:}{ object of class \code{"matrix"}:
+ standardizing matrix. }
+
+ \item{\code{weight}:}{ object of class \code{"RobWeight"}:
+ weight function }
+
+ \item{\code{biastype}:}{ object of class \code{"BiasType"}:
+ bias type (symmetric/onsided/asymmetric) }
+ \item{\code{normtype}:}{ object of class \code{"NormType"}:
+ norm type (Euclidean, information/self-standardized)}
+
+ \item{\code{lowerCase}:}{ object of class \code{"OptionalNumeric"}:
+ optional constant for lower case solution. }
+
+ \item{\code{neighborRadius}:}{ object of class \code{"numeric"}:
+ radius of the corresponding (unconditional) contamination
+ neighborhood. }
+ }
+}
+\section{Extends}{
+Class \code{"IC"}, directly.\cr
+Class \code{"InfluenceCurve"}, by class \code{"IC"}.
+}
+\section{Methods}{
+ \describe{
+
+ \item{stand}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{stand}. }
+
+ \item{weight}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{weight}. }
+
+ \item{biastype}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{biastype}. }
+ \item{normtype}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{normtype}. }
+ \item{lowerCase}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{lowerCase}. }
+
+ \item{neighborRadius}{\code{signature(object = "HampIC")}:
+ accessor function for slot \code{neighborRadius}. }
+
+ \item{neighborRadius<-}{\code{signature(object = "HampIC")}:
+ replacement function for slot \code{neighborRadius}. }
+
+ }
+}
+\references{
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Kohl, M. (2005) \emph{Numerical Hampributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Peter Ruckdeschel \email{Peter Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\seealso{\code{\link{IC-class}}}
+\examples{
+IC1 <- new("HampIC")
+plot(IC1)
+}
+\concept{influence curve}
+\keyword{classes}
Modified: pkg/RobAStBase/man/RobWeight-class.Rd
===================================================================
--- pkg/RobAStBase/man/RobWeight-class.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/RobWeight-class.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -2,11 +2,12 @@
\docType{class}
\alias{RobWeight-class}
\alias{name,RobWeight-method}
+\alias{name<-,RobWeight-method}
\alias{weight,RobWeight-method}
-\alias{name<-,RobWeight-method}
+\alias{weight}
+\alias{weight<--methods}
\alias{weight<-,RobWeight-method}
\alias{weight<-}
-\alias{weight}
\title{Robust Weight classes}
\description{Classes for robust weights.}
@@ -28,11 +29,10 @@
replacement function for slot \code{name}. }
\item{weight}{\code{signature(object = "RobWeight")}:
- accessor function for slot \code{name}. }
+ accessor function for slot \code{weight}. }
- \item{weight<-}{\code{signature(object = "RobWeight", value = "function")}:
+ \item{weight<-}{\code{signature(object = "RobWeight", value = "ANY")}:
replacement function for slot \code{weight}. }
-
}
}
\references{
Modified: pkg/RobAStBase/man/TotalVarIC-class.Rd
===================================================================
--- pkg/RobAStBase/man/TotalVarIC-class.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/TotalVarIC-class.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -10,14 +10,9 @@
\alias{clipUp,TotalVarIC-method}
\alias{clipUp<-}
\alias{clipUp<-,TotalVarIC-method}
-\alias{lowerCase,TotalVarIC-method}
\alias{lowerCase<-,TotalVarIC-method}
-\alias{neighborRadius,TotalVarIC-method}
-\alias{neighborRadius<-,TotalVarIC-method}
\alias{show,TotalVarIC-method}
-\alias{stand,TotalVarIC-method}
\alias{stand<-,TotalVarIC-method}
-\alias{weight,TotalVarIC-method}
\alias{generateIC,TotalVarNeighborhood,L2ParamFamily-method}
\title{Influence curve of total variation type}
@@ -69,7 +64,8 @@
}
}
\section{Extends}{
-Class \code{"IC"}, directly.\cr
+Class \code{"HampIC"}, directly.\cr
+Class \code{"IC"}, by class \code{"HampIC"}.\cr
Class \code{"InfluenceCurve"}, by class \code{"IC"}.
}
\section{Methods}{
@@ -89,21 +85,9 @@
\item{clipUp<-}{\code{signature(object = "TotalVarIC")}:
replacement function for slot \code{clipUp}. }
- \item{stand}{\code{signature(object = "TotalVarIC")}:
- accessor function for slot \code{stand}. }
-
\item{stand<-}{\code{signature(object = "TotalVarIC")}:
replacement function for slot \code{stand}. }
- \item{weight}{\code{signature(object = "TotalVarIC")}:
- accessor function for slot \code{weight}. }
-
- \item{neighborRadius}{\code{signature(object = "TotalVarIC")}:
- accessor function for slot \code{neighborRadius}. }
-
- \item{neighborRadius<-}{\code{signature(object = "TotalVarIC")}:
- replacement function for slot \code{neighborRadius}. }
-
\item{generateIC}{\code{signature(neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily")}:
generate an object of class \code{"TotalVarIC"}. Rarely called directly. }
@@ -118,7 +102,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{IC-class}}, \code{\link{ContIC}}}
+\seealso{\code{\link{IC-class}}, \code{\link{ContIC}}, \code{\link{HampIC-class}}}
\examples{
IC1 <- new("TotalVarIC")
plot(IC1)
Added: pkg/RobAStBase/man/getBiasIC.Rd
===================================================================
--- pkg/RobAStBase/man/getBiasIC.Rd (rev 0)
+++ pkg/RobAStBase/man/getBiasIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,65 @@
+\name{getBiasIC}
+\alias{getBiasIC}
+\alias{getBiasIC-methods}
+\alias{getBiasIC,IC,UncondNeighborhood-method}
+
+\title{Generic function for the computation of the asymptotic bias for an IC}
+\description{
+ Generic function for the computation of the asymptotic bias for an IC.
+}
+\usage{
+getBiasIC(IC, neighbor, ...)
+
+\S4method{getBiasIC}{IC,UncondNeighborhood}(IC, neighbor, L2Fam, biastype = symmetricBias(),
+ normtype = NormType(), tol = .Machine$double.eps^0.25)
+}
+\arguments{
+ \item{IC}{ object of class \code{"InfluenceCurve"} }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{\dots}{ additional parameters }
+ \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
+ \item{biastype}{object of class \code{"BiasType"}}
+ \item{normtype}{object of class \code{"NormType"}}
+ \item{tol}{ the desired accuracy (convergence tolerance).}
+}
+\details{}
+\value{The bias of the IC is computed.}
+\section{Methods}{
+\describe{
+ \item{IC = "IC", neighbor = "UncondNeighborhood"}{
+ determines the as. bias by random evaluation of the IC;
+ this random evaluation is done by the internal S4-method
+ \code{.evalBiasIC}; this latter dispatches according to
+ the signature \code{IC, neighbor, biastype}.\cr
+ For signature \code{IC="IC", neighbor = "ContNeighborhood",
+ biastype = "BiasType"}, also an argument \code{normtype}
+ is used to be able to use self- or information standardizing
+ norms; besides this the signatures
+ \code{IC="IC", neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"},
+ \code{IC="IC", neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"}, and
+ \code{IC="IC", neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"} are implemented.
+ }
+}}
+\references{
+ Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+ Verw. Geb. \bold{10}:269--278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Bias
+ of M-estimators on Neighborhoods.
+}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+\note{This generic function is still under construction.}
+\seealso{\code{\link{getRiskIC-methods}}, \code{\link{InfRobModel-class}}}
+%\examples{}
+\concept{influence curve}
+\keyword{}
Added: pkg/RobAStBase/man/getRiskIC.Rd
===================================================================
--- pkg/RobAStBase/man/getRiskIC.Rd (rev 0)
+++ pkg/RobAStBase/man/getRiskIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,122 @@
+\name{getRiskIC}
+\alias{getRiskIC}
+\alias{getRiskIC-methods}
+\alias{getRiskIC,IC,asCov,missing,missing-method}
+\alias{getRiskIC,IC,asCov,missing,L2ParamFamily-method}
+\alias{getRiskIC,IC,trAsCov,missing,missing-method}
+\alias{getRiskIC,IC,trAsCov,missing,L2ParamFamily-method}
+\alias{getRiskIC,IC,asBias,UncondNeighborhood,missing-method}
+\alias{getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method}
+\alias{getRiskIC,IC,asMSE,UncondNeighborhood,missing-method}
+\alias{getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method}
+\alias{getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method}
+\alias{getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method}
+\alias{getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method}
+
+\title{Generic function for the computation of a risk for an IC}
+\description{
+ Generic function for the computation of a risk for an IC.
+}
+\usage{
+getRiskIC(IC, risk, neighbor, L2Fam, ...)
+
+\S4method{getRiskIC}{IC,asCov,missing,missing}(IC, risk, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,asCov,missing,L2ParamFamily}(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,trAsCov,missing,missing}(IC, risk, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,trAsCov,missing,L2ParamFamily}(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+
+\S4method{getRiskIC}{TotalVarIC,asUnOvShoot,UncondNeighborhood,missing}(IC, risk, neighbor)
+
+\S4method{getRiskIC}{IC,fiUnOvShoot,ContNeighborhood,missing}(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+\S4method{getRiskIC}{IC,fiUnOvShoot,TotalVarNeighborhood,missing}(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+}
+\arguments{
+ \item{IC}{ object of class \code{"InfluenceCurve"} }
+ \item{risk}{ object of class \code{"RiskType"}. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
+ \item{\dots}{ additional parameters }
+ \item{tol}{ the desired accuracy (convergence tolerance).}
+ \item{sampleSize}{ integer: sample size. }
+ \item{Algo}{ "A" or "B". }
+ \item{cont}{ "left" or "right". }
+}
+\details{To make sure that the results are valid, it is recommended
+ to include an additional check of the IC properties of \code{IC}
+ using \code{checkIC}.}
+\value{The risk of an IC is computed.}
+\section{Methods}{
+\describe{
+ \item{IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"}{
+ asymptotic covariance of \code{IC}. }
+
+ \item{IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"}{
+ asymptotic covariance of \code{IC} under \code{L2Fam}. }
+
+ \item{IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"}{
+ asymptotic covariance of \code{IC}. }
+
+ \item{IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"}{
+ asymptotic covariance of \code{IC} under \code{L2Fam}. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"}{
+ asymptotic bias of \code{IC} under convex contaminations; uses method \code{\link{getBiasIC}}. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"}{
+ asymptotic bias of \code{IC} under convex contaminations and \code{L2Fam}; uses method \code{\link{getBiasIC}}. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"}{
+ asymptotic bias of \code{IC} in case of total variation neighborhoods; uses method \code{\link{getBiasIC}}. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"}{
+ asymptotic bias of \code{IC} under \code{L2Fam} in case of total variation
+ neighborhoods; uses method \code{\link{getBiasIC}}. }
+
+ \item{IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"}{
+ asymptotic mean square error of \code{IC}. }
+
+ \item{IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"}{
+ asymptotic mean square error of \code{IC} under \code{L2Fam}. }
+
+ \item{IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"}{
+ asymptotic under-/overshoot risk of \code{IC}. }
+
+ \item{IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"}{
+ finite-sample under-/overshoot risk of \code{IC}. }
+
+ \item{IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"}{
+ finite-sample under-/overshoot risk of \code{IC}. }
+}}
+\references{
+ Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+ Verw. Geb. \bold{10}:269--278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+ of M-estimators on Neighborhoods.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}\cr
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+\note{This generic function is still under construction.}
+\seealso{\code{\link[ROptEst]{getRiskIC-methods}}, \code{\link{InfRobModel-class}}}
+%\examples{}
+\concept{influence curve}
+\keyword{}
Modified: pkg/RobAStBase/man/getweight.Rd
===================================================================
--- pkg/RobAStBase/man/getweight.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/getweight.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -22,6 +22,10 @@
minbiasweight(Weight, neighbor, biastype, ...)
\S4method{getweight}{HampelWeight,ContNeighborhood,BiasType}(Weight, neighbor, biastype, normtype)
\S4method{minbiasweight}{HampelWeight,ContNeighborhood,BiasType}(Weight, neighbor, biastype, normtype)
+\S4method{getweight}{HampelWeight,ContNeighborhood,onesidedBias}(Weight, neighbor, biastype, ...)
+\S4method{minbiasweight}{HampelWeight,ContNeighborhood,onesidedBias}(Weight, neighbor, biastype,...)
+\S4method{getweight}{HampelWeight,ContNeighborhood,asymmetricBias}(Weight, neighbor, biastype, ...)
+\S4method{minbiasweight}{HampelWeight,ContNeighborhood,asymmetricBias}(Weight, neighbor, biastype,...)
}
\arguments{
\item{\dots}{ additional arguments }
@@ -29,6 +33,7 @@
\item{neighbor}{ Object of class \code{"Neighborhood"}. }
\item{biastype}{ Object of class \code{"BiasType"}. }
\item{normtype}{ Object of class \code{"NormType"} --- only for signature \code{HampelWeight,ContNeighborhood,BiasType}. }
+ \item{\dots}{possibly additional (unused) arguments --- like in a call to the less specific methods.}
}
%\details{}
\value{Object of class \code{"HampelWeight"} resp. \code{"BdStWeight"}}
Added: pkg/RobAStBase/man/internals.Rd
===================================================================
--- pkg/RobAStBase/man/internals.Rd (rev 0)
+++ pkg/RobAStBase/man/internals.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,40 @@
+\name{internals_for_RobAStBase}
+\alias{internals_for_RobAStBase}
+\alias{.eq}
+\alias{.getDistr}
+
+\title{Internal / Helper functions of package RobAStBase}
+
+\description{
+These functions are used internally by package RobAStBase.}
+
+\usage{
+.eq(x,y = 0*x, tol = 1e-7)
+.getDistr(L2Fam)
+}
+
+\arguments{
+ \item{x}{a (numeric) vector}
+ \item{y}{a (numeric) vector}
+ \item{tol}{numeric --- tolerance}
+ \item{L2fam}{object of class \code{L2ParamFamily}}
+}
+
+\details{
+\code{.eq}checks equality of two vectors up to a given precision;
+\code{.getDistr} produces a string with the class of the family and its parameter value;
+}
+
+
+\value{
+\item{.eq}(a vector of) \code{logical}.
+\item{.getDistr} \code{character}
+}
+
+
+\author{
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+ }
+
+\keyword{internal}
+\concept{utilities}
\ No newline at end of file
Added: pkg/RobAStBase/man/makeIC-methods.Rd
===================================================================
--- pkg/RobAStBase/man/makeIC-methods.Rd (rev 0)
+++ pkg/RobAStBase/man/makeIC-methods.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -0,0 +1,41 @@
+\name{makeIC-methods}
+\docType{methods}
+\alias{makeIC}
+\alias{makeIC-methods}
+\alias{makeIC,IC,missing-method}
+\alias{makeIC,IC,L2ParamFamily-method}
+
+\title{Generic Function for making ICs consistent at a possibly different model}
+\description{
+ Generic function for providing centering and Fisher consistency of ICs.
+}
+\usage{
+makeIC(IC, L2Fam, ...)
+}
+\arguments{
+ \item{IC}{ object of class \code{"IC"} }
+ \item{L2Fam}{ L2-differentiable family of probability measures; may be missing. }
+ \item{\dots}{ additional parameters }
+}
+\value{An IC at the model.}
+\section{Methods}{\describe{
+\item{makeIC}{\code{signature(IC = "IC", L2Fam = "missing"}: ...}
+\item{makeIC}{\code{signature(IC = "IC", L2Fam = "L2ParamFamily"}: ...}
+}}
+
+\references{
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\seealso{\code{\link[distrMod]{L2ParamFamily-class}}, \code{\link{IC-class}}}
+\examples{
+IC1 <- new("IC")
+B <- BinomFamily(13, 0.3)
+makeIC(IC1,B)
+}
+\concept{influence curve}
+\keyword{}
Deleted: pkg/RobAStBase/man/makeIC.Rd
===================================================================
--- pkg/RobAStBase/man/makeIC.Rd 2008-03-26 01:14:35 UTC (rev 79)
+++ pkg/RobAStBase/man/makeIC.Rd 2008-03-28 02:21:40 UTC (rev 80)
@@ -1,41 +0,0 @@
-\name{makeIC-methods}
-\docType{methods}
-\alias{makeIC}
-\alias{makeIC-methods}
-\alias{makeIC,IC,missing-method}
-\alias{makeIC,IC,L2ParamFamily-method}
-
-\title{Generic Function for making ICs consistent at a possibly different model}
-\description{
- Generic function for providing centering and Fisher consistency of ICs.
-}
-\usage{
-makeIC(IC, L2Fam, ...)
-}
-\arguments{
- \item{IC}{ object of class \code{"IC"} }
- \item{L2Fam}{ L2-differentiable family of probability measures; may be missing. }
- \item{\dots}{ additional parameters }
-}
-\value{An IC at the model.}
-\section{Methods}{\describe{
-\item{makeIC}{\code{signature(IC = "IC", L2Fam = "missing"}: ...}
-\item{makeIC}{\code{signature(IC = "IC", L2Fam = "L2ParamFamily"}: ...}
-}}
-
-\references{
- Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
-%\note{}
-\seealso{\code{\link[distrMod]{L2ParamFamily-class}}, \code{\link{IC-class}}}
-\examples{
-IC1 <- new("IC")
-B <- BinomFamily(13, 0.3)
-makeIC(IC1,B)
-}
-\concept{influence curve}
-\keyword{}
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