[Robast-commits] r334 - in branches/robast-0.7/pkg: ROptEst/R ROptEst/chm ROptEst/man RobAStBase/R RobAStBase/chm

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Aug 4 06:58:47 CEST 2009


Author: ruckdeschel
Date: 2009-08-04 06:58:45 +0200 (Tue, 04 Aug 2009)
New Revision: 334

Modified:
   branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asCov.R
   branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asGRisk.R
   branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asHampel.R
   branches/robast-0.7/pkg/ROptEst/chm/00Index.html
   branches/robast-0.7/pkg/ROptEst/chm/ROptEst.chm
   branches/robast-0.7/pkg/ROptEst/chm/ROptEst.toc
   branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html
   branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd
   branches/robast-0.7/pkg/RobAStBase/R/Weights.R
   branches/robast-0.7/pkg/RobAStBase/chm/RobAStBase.chm
Log:
RobAstBase/ROptEst: we now can digest case p=1, k>1 for asymmetric biastypes as well as for total variation

Modified: branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asCov.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asCov.R	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asCov.R	2009-08-04 04:58:45 UTC (rev 334)
@@ -24,7 +24,8 @@
             clip(w) <- b
             cent(w) <- 0
             stand(w) <- A
-            weight(w) <- getweight(w, neighbor = neighbor, biastype = symmetricBias(), 
+            weight(w) <- getweight(w, neighbor = neighbor,
+                                   biastype = symmetricBias(),
                                    normW = NormType())
 
             return(list(A = A, a = 0, b = b, d = NULL, w = w, risk = Risk, info = info))
@@ -51,16 +52,22 @@
             w <- new("BdStWeight")
             clip(w) <- c(0,b)+a
             stand(w) <- A
-            weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype, 
+            weight(w) <- getweight(w, neighbor = neighbor,
+                                   biastype = symmetricBias(),
                                    normW = NormType())
 
             return(list(A = A, a = -b/2, b = b, d = NULL, w = w, risk = Risk, info = info))
     })
 setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable", 
                                    risk = "asCov", 
-                                   neighbor = "ContNeighborhood"),
+                                   neighbor = "UncondNeighborhood"),
     function(L2deriv, risk, neighbor, Distr, Finfo, trafo, 
              QuadForm = diag(nrow(trafo)), verbose = FALSE){
+
+            Cont <- is(neighbor,"ContNeighborhood")
+            p <- nrow(trafo)
+            if(! Cont && p>1)
+                 stop("Not yet implemented")
             info <- c("optimal IC in sense of Cramer-Rao bound")
             A <- trafo %*% solve(Finfo)
             IC <- A %*% L2deriv
@@ -69,8 +76,12 @@
                 upper <- ifelse(is.finite(q(Distr)(1)), q(Distr)(1-1e-8), q(Distr)(1))
                 x <- seq(from = lower, to = upper, length = 1e5)
                 x <- x[x!=0] # problems with NaN=log(0)!
-                b <- evalRandVar(IC, as.matrix(x))^2
-                b <- sqrt(max(colSums(b, na.rm = TRUE)))
+                ICx <- evalRandVar(IC, as.matrix(x))
+                if(Cont)
+                   b <- sqrt(max(colSums(ICx^2, na.rm = TRUE)))
+                else{
+                   b <- max(ICx)-min(ICx)
+                }
             }else{
                 b <- Inf # not yet implemented
             }
@@ -88,13 +99,18 @@
                          asMSE = list(value = trAsCov + r^2*b^2, 
                                       r = r,
                                       at = neighbor))
-            w <- new("HampelWeight")
-            clip(w) <- b
-            cent(w) <- 0
-            stand(w) <- A
-            weight(w) <- getweight(w, neighbor = neighbor, biastype = symmetricBias(), 
+            if(Cont){
+               w <- new("HampelWeight")
+               clip(w) <- b
+               cent(w) <- 0
+               stand(w) <- A
+            }else{
+               w <- new("BdStWeight")
+               clip(w) <- c(0,b)+as.numeric(A%*%z)
+               stand(w) <- A
+            }
+            weight(w) <- getweight(w, neighbor = neighbor, biastype = symmetricBias(),
                                    normW = NormType())
-
-            return(list(A = A, a = numeric(nrow(trafo)), b = b, d = NULL, w = w, risk = Risk, 
+            return(list(A = A, a = numeric(nrow(trafo)), b = b, d = NULL, w = w, risk = Risk,
                         info = info))
     })

Modified: branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asGRisk.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asGRisk.R	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asGRisk.R	2009-08-04 04:58:45 UTC (rev 334)
@@ -143,12 +143,15 @@
 
 setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable", 
                                    risk = "asGRisk", 
-                                   neighbor = "ContNeighborhood"),
+                                   neighbor = "UncondNeighborhood"),
     function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
              L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, 
              z.start, A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE){
         biastype <- biastype(risk)
         normtype <- normtype(risk)
+        p <- nrow(trafo)
+        if(! is(neighbor,"ContNeighborhood") && p>1)
+           stop("Not yet implemented")
 
         FI <- solve(trafo%*%solve(Finfo)%*%t(trafo))
         if(is(normtype,"InfoNorm") || is(normtype,"SelfNorm") ) 
@@ -189,7 +192,11 @@
         z.comp <- comp$"z.comp"
         A.comp <- comp$"A.comp"
 
-        w <- new("HampelWeight")
+        if(is(neighbor,"ContNeighborhood")){
+            w <- new("HampelWeight")
+        }else{
+            w <- new("BdStWeight")
+        }
         z <- z.start
         A <- A.start
         b <- 0
@@ -201,8 +208,9 @@
             b.old <- b
             A.old <- A
             ##
-            cent(w) <- z 
-            stand(w) <- A 
+            if(is(neighbor,"ContNeighborhood"))
+               cent(w) <- z
+            stand(w) <- A
 
             ## new
             lower0 <- getL1normL2deriv(L2deriv = L2deriv, cent = z, stand = A, 
@@ -248,7 +256,11 @@
                 }
                 return(res)
             }
-            clip(w) <- b
+            if(is(neighbor,"ContNeighborhood")){
+                clip(w) <- b
+            }else{
+                clip(w) <- c(0,b)+as.numeric(A%*%z) ## =a
+            }
 
 
             weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype, 

Modified: branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asHampel.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asHampel.R	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asHampel.R	2009-08-04 04:58:45 UTC (rev 334)
@@ -130,7 +130,7 @@
 
 setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable", 
                                    risk = "asHampel", 
-                                   neighbor = "ContNeighborhood"),
+                                   neighbor = "UncondNeighborhood"),
     function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
              L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE,
              z.start, A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE,
@@ -139,6 +139,8 @@
         biastype <- biastype(risk)
         normtype <- normtype(risk)
         p <- nrow(trafo)
+        if(! is(neighbor,"ContNeighborhood") && p>1)
+           stop("Not yet implemented")
 
         FI <- solve(trafo%*%solve(Finfo)%*%t(trafo))
         if(is(normtype,"InfoNorm") || is(normtype,"SelfNorm") ) 
@@ -151,71 +153,81 @@
         b <- risk at bound
 
         if(checkBounds){
-        ClassIC <- trafo %*% solve(Finfo) %*% L2deriv
-        lower.x <- q(Distr)(getdistrOption("TruncQuantile"))
-        upper.x <- q(Distr)(1-getdistrOption("TruncQuantile"))
-        x <- seq(from = lower.x, to = upper.x, length = 1000)
-        bmax <- sapply(x,function(x) evalRandVar(ClassIC,x))
-        bmax <- sqrt(max(colSums(bmax^2)))
-        cat("numerical approximation of maximal bound:\t", bmax, "\n")
-        if(b >= bmax){
-            if(warn) cat("'b >= maximum asymptotic bias' => (classical) optimal IC\n", 
-                         "in sense of Cramer-Rao bound is returned\n")
-            res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(), neighbor = neighbor, 
-                                Distr = Distr, Finfo = Finfo, trafo = trafo, 
-                                QuadForm = std, verbose = verbose)
-            res <- c(res, list(biastype = biastype, normtype = normtype))
-            trAsCov <- sum(diag(std%*%res$risk$asCov)); 
-            r <- neighbor at radius
-            res$risk$trAsCov <- list(value = trAsCov, normtype = normtype)
-            res$risk$asBias <- list(value = b, biastype = biastype, 
-                                   normtype = normtype, 
-                                   neighbortype = class(neighbor))
-            res$risk$asMSE <- list(value = trAsCov + r^2*b^2, 
-                                   r = r,
-                                   at = neighbor)
-            return(res)
-        }
+            ClassIC <- trafo %*% solve(Finfo) %*% L2deriv
+            lower.x <- q(Distr)(getdistrOption("TruncQuantile"))
+            upper.x <- q(Distr)(1-getdistrOption("TruncQuantile"))
+            x <- seq(from = lower.x, to = upper.x, length = 1000)
+            bmax <- sapply(x,function(x) evalRandVar(ClassIC,x))
+            bmax <- sqrt(max(colSums(bmax^2)))
+            cat("numerical approximation of maximal bound:\t", bmax, "\n")
+            if(b >= bmax){
+                if(warn) cat("'b >= maximum asymptotic bias' => (classical) optimal IC\n",
+                             "in sense of Cramer-Rao bound is returned\n")
+                res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(), neighbor = neighbor,
+                                    Distr = Distr, Finfo = Finfo, trafo = trafo,
+                                    QuadForm = std, verbose = verbose)
+                res <- c(res, list(biastype = biastype, normtype = normtype))
+                trAsCov <- sum(diag(std%*%res$risk$asCov));
+                r <- neighbor at radius
+                res$risk$trAsCov <- list(value = trAsCov, normtype = normtype)
+                res$risk$asBias <- list(value = b, biastype = biastype,
+                                       normtype = normtype,
+                                       neighbortype = class(neighbor))
+                res$risk$asMSE <- list(value = trAsCov + r^2*b^2,
+                                       r = r,
+                                       at = neighbor)
+                return(res)
+            }
 
-        res <- getInfRobIC(L2deriv = L2deriv, 
-                     risk = asBias(biastype = biastype, normtype = normtype), 
-                     neighbor = neighbor, Distr = Distr, DistrSymm = DistrSymm, 
-                     L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm, 
-                     z.start = z.start, A.start = A.start, trafo = trafo, 
-                     maxiter = maxiter, tol = tol, warn = warn, Finfo = Finfo, 
-                     verbose = verbose)
-        bmin <- res$b
+            res <- getInfRobIC(L2deriv = L2deriv,
+                         risk = asBias(biastype = biastype, normtype = normtype),
+                         neighbor = neighbor, Distr = Distr, DistrSymm = DistrSymm,
+                         L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
+                         z.start = z.start, A.start = A.start, trafo = trafo,
+                         maxiter = maxiter, tol = tol, warn = warn, Finfo = Finfo,
+                         verbose = verbose)
+            bmin <- res$b
 
-        cat("minimal bound:\t", bmin, "\n")
-        if(b <= bmin){
-            if(warn) cat("'b <= minimum asymptotic bias'\n",
-                         "=> the minimum asymptotic bias (lower case) solution is returned\n")
+            cat("minimal bound:\t", bmin, "\n")
+            if(b <= bmin){
+                if(warn) cat("'b <= minimum asymptotic bias'\n",
+                             "=> the minimum asymptotic bias (lower case) solution is returned\n")
 
-            asMSE <- sum(diag(std%*%res$risk$asCov)) + neighbor at radius^2*bmin^2
-            if(!is.null(res$risk$asMSE)) res$risk$asMSE <- asMSE 
-               else     res$risk <- c(list(asMSE = asMSE), res$risk)
+                asMSE <- sum(diag(std%*%res$risk$asCov)) + neighbor at radius^2*bmin^2
+                if(!is.null(res$risk$asMSE)) res$risk$asMSE <- asMSE
+                   else     res$risk <- c(list(asMSE = asMSE), res$risk)
 
-            return(res)
+                return(res)
+            }
         }
-        }
 
         comp <- .getComp(L2deriv, DistrSymm, L2derivSymm, L2derivDistrSymm)
 
         z.comp <- comp$"z.comp"
         A.comp <- comp$"A.comp"
 
-        w <- new("HampelWeight")
-        clip(w) <- b
         z <- z.start
         A <- A.start
+        if(is(neighbor,"ContNeighborhood")){
+            w <- new("HampelWeight")
+        }else{
+            w <- new("BdStWeight")
+        }
         iter <- 0
         repeat{
             iter <- iter + 1
             z.old <- z
             A.old <- A
-            cent(w) <- z 
-            stand(w) <- A 
 
+            if(is(neighbor,"ContNeighborhood")){
+                clip(w) <- b
+                cent(w) <- z
+                stand(w) <- A
+            }else{
+                clip(w) <- c(0,b)+as.numeric(A%*%z)
+                stand(w) <- A
+            }
+
             weight(w) <- getweight(w, neighbor = neighbor, biastype = biastype, 
                                    normW = normtype)
 

Modified: branches/robast-0.7/pkg/ROptEst/chm/00Index.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/00Index.html	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/chm/00Index.html	2009-08-04 04:58:45 UTC (rev 334)
@@ -173,11 +173,11 @@
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
 <tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
-<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asCov,UncondNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
-<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asGRisk,UncondNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
-<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
 <tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>

Modified: branches/robast-0.7/pkg/ROptEst/chm/ROptEst.chm
===================================================================
(Binary files differ)

Modified: branches/robast-0.7/pkg/ROptEst/chm/ROptEst.toc
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/ROptEst.toc	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/chm/ROptEst.toc	2009-08-04 04:58:45 UTC (rev 334)
@@ -282,15 +282,15 @@
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method">
+<param name="Name" value="getInfRobIC,RealRandVariable,asCov,UncondNeighborhood-method">
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method">
+<param name="Name" value="getInfRobIC,RealRandVariable,asGRisk,UncondNeighborhood-method">
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method">
+<param name="Name" value="getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method">
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">

Modified: branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html	2009-08-04 04:58:45 UTC (rev 334)
@@ -9,13 +9,13 @@
 <param name="keyword" value="R:   getInfRobIC-methods">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method">
-<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method">
+<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asCov,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method">
-<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method">
+<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method">
-<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method">
+<param name="keyword" value="R:   getInfRobIC,RealRandVariable,asGRisk,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method">
 <param name="keyword" value=" Generic Function for the Computation of Optimally Robust ICs">
 </object>
@@ -40,52 +40,66 @@
 
 ## S4 method for signature 'UnivariateDistribution, asCov,
 ##   ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo, verbose = FALSE)
+getInfRobIC(L2deriv,
+                       risk, neighbor, Finfo, trafo, verbose = FALSE)
 
 ## S4 method for signature 'UnivariateDistribution, asCov,
 ##   TotalVarNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo, verbose = FALSE)
+getInfRobIC(L2deriv,
+                       risk, neighbor, Finfo, trafo, verbose = FALSE)
 
 ## S4 method for signature 'RealRandVariable, asCov,
-##   ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo, 
+##   UncondNeighborhood':
+getInfRobIC(L2deriv, risk,
+                       neighbor, Distr, Finfo, trafo,
                        QuadForm = diag(nrow(trafo)), verbose = FALSE)
 
 ## S4 method for signature 'UnivariateDistribution, asBias,
 ##   UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, trafo, 
-             maxiter, tol, warn, Finfo, verbose = FALSE, ...)
+getInfRobIC(L2deriv,
+                       risk, neighbor, symm, trafo,
+                       maxiter, tol, warn, Finfo, verbose = FALSE, ...)
 
 ## S4 method for signature 'RealRandVariable, asBias,
 ##   ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, z.start, A.start, Finfo, trafo, maxiter, tol, warn, verbose = FALSE, ...)
+getInfRobIC(L2deriv, risk,
+                       neighbor, Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, z.start, A.start, Finfo, trafo,
+                       maxiter, tol, warn, verbose = FALSE, ...)
 
 ## S4 method for signature 'UnivariateDistribution,
 ##   asHampel, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper = NULL, maxiter, tol, warn, noLow = FALSE, verbose = FALSE, checkBounds = TRUE)
+getInfRobIC(L2deriv,
+                       risk, neighbor, symm, Finfo, trafo, upper = NULL, maxiter,
+                       tol, warn, noLow = FALSE, verbose = FALSE, checkBounds = TRUE)
 
 ## S4 method for signature 'RealRandVariable, asHampel,
-##   ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper = NULL, maxiter, tol, warn,
-             verbose = FALSE, checkBounds = TRUE)
+##   UncondNeighborhood':
+getInfRobIC(L2deriv, risk,
+                       neighbor, Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start,
+                       A.start, upper = NULL, maxiter, tol, warn,
+                       verbose = FALSE, checkBounds = TRUE)
 
 ## S4 method for signature 'UnivariateDistribution,
 ##   asGRisk, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper = NULL, maxiter, tol, warn, noLow = FALSE, verbose = FALSE)
+getInfRobIC(L2deriv,
+                       risk, neighbor, symm, Finfo, trafo,
+                       upper = NULL, maxiter, tol, warn, noLow = FALSE,
+                       verbose = FALSE)
 
 ## S4 method for signature 'RealRandVariable, asGRisk,
-##   ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor,  Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE)
+##   UncondNeighborhood':
+getInfRobIC(L2deriv, risk,
+                       neighbor,  Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start,
+                       A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE)
 
 ## S4 method for signature 'UnivariateDistribution,
 ##   asUnOvShoot, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper, maxiter, tol, warn)
+getInfRobIC(
+                       L2deriv, risk, neighbor, symm, Finfo, trafo,
+                       upper, maxiter, tol, warn)
 </pre>
 
 
@@ -183,9 +197,12 @@
 
 
 <dt>L2deriv = "RealRandVariable", risk = "asCov", 
-neighbor = "ContNeighborhood"</dt><dd>computes the classical optimal influence curve for L2 differentiable 
+neighbor = "UncondNeighborhood"</dt><dd>computes the classical optimal influence curve for L2 differentiable 
 parametric families with unknown <i>k</i>-dimensional parameter 
-(<i>k &gt; 1</i>) where the underlying distribution is univariate. </dd>
+(<i>k &gt; 1</i>) where the underlying distribution is univariate;
+for total variation neighborhoods only is implemented for the case
+where there is a <i>1 x k</i> transformation <code>trafo</code>
+matrix. </dd>
 
 
 <dt>L2deriv = "UnivariateDistribution", risk = "asBias", 
@@ -205,9 +222,12 @@
 
 
 <dt>L2deriv = "RealRandVariable", risk = "asHampel", 
-neighbor = "ContNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable 
+neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable 
 parametric families with unknown <i>k</i>-dimensional parameter 
-(<i>k &gt; 1</i>) where the underlying distribution is univariate. </dd>
+(<i>k &gt; 1</i>) where the underlying distribution is univariate;
+for total variation neighborhoods only is implemented for the case
+where there is a <i>1 x k</i> transformation <code>trafo</code>
+matrix. </dd>
 
 
 <dt>L2deriv = "UnivariateDistribution", risk = "asGRisk", 
@@ -216,9 +236,12 @@
 
 
 <dt>L2deriv = "RealRandVariable", risk = "asGRisk", 
-neighbor = "ContNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable 
+neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable 
 parametric families with unknown <i>k</i>-dimensional parameter 
-(<i>k &gt; 1</i>) where the underlying distribution is univariate. </dd>
+(<i>k &gt; 1</i>) where the underlying distribution is univariate;
+for total variation neighborhoods only is implemented for the case
+where there is a <i>1 x k</i> transformation <code>trafo</code>
+matrix. </dd>
 
 
 <dt>L2deriv = "UnivariateDistribution", risk = "asUnOvShoot", 
@@ -230,7 +253,8 @@
 <h3>Author(s)</h3>
 
 <p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+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 itwm.fraunhofer.de">Peter.Ruckdeschel at itwm.fraunhofer.de</a>
 </p>
 
 

Modified: branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd
===================================================================
--- branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd	2009-07-31 21:59:27 UTC (rev 333)
+++ branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd	2009-08-04 04:58:45 UTC (rev 334)
@@ -3,13 +3,13 @@
 \alias{getInfRobIC-methods}
 \alias{getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method}
-\alias{getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method}
+\alias{getInfRobIC,RealRandVariable,asCov,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method}
 \alias{getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method}
-\alias{getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method}
+\alias{getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method}
-\alias{getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method}
+\alias{getInfRobIC,RealRandVariable,asGRisk,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method}
 
 \title{ Generic Function for the Computation of Optimally Robust ICs }
@@ -21,34 +21,48 @@
 \usage{
 getInfRobIC(L2deriv, risk, neighbor, ...)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asCov,ContNeighborhood}(L2deriv, risk, neighbor, Finfo, trafo, verbose = FALSE)
+\S4method{getInfRobIC}{UnivariateDistribution,asCov,ContNeighborhood}(L2deriv,
+                       risk, neighbor, Finfo, trafo, verbose = FALSE)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asCov,TotalVarNeighborhood}(L2deriv, risk, neighbor, Finfo, trafo, verbose = FALSE)
+\S4method{getInfRobIC}{UnivariateDistribution,asCov,TotalVarNeighborhood}(L2deriv,
+                       risk, neighbor, Finfo, trafo, verbose = FALSE)
 
-\S4method{getInfRobIC}{RealRandVariable,asCov,ContNeighborhood}(L2deriv, risk, neighbor, Distr, Finfo, trafo, 
+\S4method{getInfRobIC}{RealRandVariable,asCov,UncondNeighborhood}(L2deriv, risk,
+                       neighbor, Distr, Finfo, trafo,
                        QuadForm = diag(nrow(trafo)), verbose = FALSE)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv, risk, neighbor, symm, trafo, 
-             maxiter, tol, warn, Finfo, verbose = FALSE, ...)
+\S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv,
+                       risk, neighbor, symm, trafo,
+                       maxiter, tol, warn, Finfo, verbose = FALSE, ...)
 
-\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, z.start, A.start, Finfo, trafo, maxiter, tol, warn, verbose = FALSE, ...)
+\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk,
+                       neighbor, Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, z.start, A.start, Finfo, trafo,
+                       maxiter, tol, warn, verbose = FALSE, ...)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper = NULL, maxiter, tol, warn, noLow = FALSE, verbose = FALSE, checkBounds = TRUE)
+\S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv,
+                       risk, neighbor, symm, Finfo, trafo, upper = NULL, maxiter,
+                       tol, warn, noLow = FALSE, verbose = FALSE, checkBounds = TRUE)
 
-\S4method{getInfRobIC}{RealRandVariable,asHampel,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper = NULL, maxiter, tol, warn,
-             verbose = FALSE, checkBounds = TRUE)
+\S4method{getInfRobIC}{RealRandVariable,asHampel,UncondNeighborhood}(L2deriv, risk,
+                       neighbor, Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start,
+                       A.start, upper = NULL, maxiter, tol, warn,
+                       verbose = FALSE, checkBounds = TRUE)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asGRisk,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper = NULL, maxiter, tol, warn, noLow = FALSE, verbose = FALSE)
+\S4method{getInfRobIC}{UnivariateDistribution,asGRisk,UncondNeighborhood}(L2deriv,
+                       risk, neighbor, symm, Finfo, trafo,
+                       upper = NULL, maxiter, tol, warn, noLow = FALSE,
+                       verbose = FALSE)
 
-\S4method{getInfRobIC}{RealRandVariable,asGRisk,ContNeighborhood}(L2deriv, risk, neighbor,  Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE)
+\S4method{getInfRobIC}{RealRandVariable,asGRisk,UncondNeighborhood}(L2deriv, risk,
+                       neighbor,  Distr, DistrSymm, L2derivSymm,
+                       L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start,
+                       A.start, upper = NULL, maxiter, tol, warn, verbose = FALSE)
 
-\S4method{getInfRobIC}{UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
-             upper, maxiter, tol, warn)
+\S4method{getInfRobIC}{UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(
+                       L2deriv, risk, neighbor, symm, Finfo, trafo,
+                       upper, maxiter, tol, warn)
 }
 \arguments{
   \item{L2deriv}{ L2-derivative of some L2-differentiable family 
@@ -93,10 +107,13 @@
     parametric families with unknown one-dimensional parameter. }
 
   \item{L2deriv = "RealRandVariable", risk = "asCov", 
-        neighbor = "ContNeighborhood"}{ 
+        neighbor = "UncondNeighborhood"}{
     computes the classical optimal influence curve for L2 differentiable 
     parametric families with unknown \eqn{k}-dimensional parameter 
-    (\eqn{k > 1}) where the underlying distribution is univariate. }
+    (\eqn{k > 1}) where the underlying distribution is univariate;
+    for total variation neighborhoods only is implemented for the case
+    where there is a \eqn{1\times k}{1 x k} transformation \code{trafo}
+    matrix. }
 
   \item{L2deriv = "UnivariateDistribution", risk = "asBias", 
         neighbor = "UncondNeighborhood"}{ 
@@ -115,10 +132,13 @@
     parametric families with unknown one-dimensional parameter. }
 
   \item{L2deriv = "RealRandVariable", risk = "asHampel", 
-        neighbor = "ContNeighborhood"}{ 
+        neighbor = "UncondNeighborhood"}{
     computes the optimally robust influence curve for L2 differentiable 
     parametric families with unknown \eqn{k}-dimensional parameter 
-    (\eqn{k > 1}) where the underlying distribution is univariate. }
+    (\eqn{k > 1}) where the underlying distribution is univariate;
+    for total variation neighborhoods only is implemented for the case
+    where there is a \eqn{1\times k}{1 x k} transformation \code{trafo}
+    matrix. }
 
   \item{L2deriv = "UnivariateDistribution", risk = "asGRisk", 
         neighbor = "UncondNeighborhood"}{
@@ -126,10 +146,13 @@
     parametric families with unknown one-dimensional parameter. }
 
   \item{L2deriv = "RealRandVariable", risk = "asGRisk", 
-        neighbor = "ContNeighborhood"}{ 
+        neighbor = "UncondNeighborhood"}{
     computes the optimally robust influence curve for L2 differentiable 
     parametric families with unknown \eqn{k}-dimensional parameter 
-    (\eqn{k > 1}) where the underlying distribution is univariate. }
+    (\eqn{k > 1}) where the underlying distribution is univariate;
+    for total variation neighborhoods only is implemented for the case
+    where there is a \eqn{1\times k}{1 x k} transformation \code{trafo}
+    matrix. }
 
   \item{L2deriv = "UnivariateDistribution", risk = "asUnOvShoot", 
         neighbor = "UncondNeighborhood"}{
@@ -151,7 +174,8 @@
   Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}. 
   Bayreuth: Dissertation.
 }
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},\cr
+        Peter Ruckdeschel \email{Peter.Ruckdeschel at itwm.fraunhofer.de}}
 %\note{}
 \seealso{\code{\link[RobAStBase]{InfRobModel-class}}}
 %\examples{}

[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/robast -r 334


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