[Robast-commits] r345 - in branches/robast-0.7/pkg/ROptEst: R chm inst/scripts man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Fri Aug 21 00:18:17 CEST 2009


Author: ruckdeschel
Date: 2009-08-21 00:18:16 +0200 (Fri, 21 Aug 2009)
New Revision: 345

Modified:
   branches/robast-0.7/pkg/ROptEst/R/LowerCaseMultivariate.R
   branches/robast-0.7/pkg/ROptEst/R/getInfCent.R
   branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asBias.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/getInfCent.html
   branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html
   branches/robast-0.7/pkg/ROptEst/chm/internals.html
   branches/robast-0.7/pkg/ROptEst/chm/minmaxBias.html
   branches/robast-0.7/pkg/ROptEst/inst/scripts/NormalLocationScaleModel.R
   branches/robast-0.7/pkg/ROptEst/man/getInfCent.Rd
   branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd
   branches/robast-0.7/pkg/ROptEst/man/internals.Rd
   branches/robast-0.7/pkg/ROptEst/man/minmaxBias.Rd
Log:
implemented lower Case solution for *=v p=1 k>1
corresponding example in script NormalLocationScaleModel.R

Modified: branches/robast-0.7/pkg/ROptEst/R/LowerCaseMultivariate.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/LowerCaseMultivariate.R	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/R/LowerCaseMultivariate.R	2009-08-20 22:18:16 UTC (rev 345)
@@ -1,11 +1,11 @@
 .LowerCaseMultivariate <- function(L2deriv, neighbor, biastype,
-             normtype, Distr, trafo, z.start,
+             normtype, Distr, Finfo, trafo, z.start,
              A.start, z.comp, A.comp, maxiter, tol, verbose = FALSE){
 
         w <- new("HampelWeight")
 
         if(is.null(z.start)) z.start <- numeric(ncol(trafo))
-        if(is.null(A.start)) A.start <- trafo
+        if(is.null(A.start)) A.start <- trafo%*%solve(Finfo)
         if(is.null(A.comp)) 
            A.comp <- matrix(TRUE, nrow = nrow(trafo), ncol = ncol(trafo))
         if(is.null(z.comp)) 
@@ -67,7 +67,61 @@
                     control = list(reltol = tol, maxit = 100*maxiter),
                     L2deriv = L2deriv, Distr = Distr, trafo = trafo)
 
+
         return(list(erg=erg, w=w, normtype = normtype, z.comp = z.comp))
     }
 
 
+.LowerCaseMultivariateTV <- function(L2deriv, neighbor, biastype,
+             normtype, Distr, Finfo, trafo,
+             A.start,  maxiter, tol, verbose = FALSE){
+
+        w <- new("BdStWeight")
+        k <- ncol(trafo)
+
+        if(is.null(A.start)) A.start <- trafo%*%solve(Finfo)
+
+        pos.fct <- function(x, L2, stand){
+            X <- evalRandVar(L2, as.matrix(x))[,,1]
+            Y <- stand %*% X
+            return(Y*(Y>0))
+        }
+
+        bmin.fct <- function(param, L2deriv, Distr, trafo){
+            p <- 1
+            A <- matrix(param, ncol = k, nrow = 1)
+         #   print(A)
+            E1 <- E(object = Distr, fun = pos.fct, L2 = L2deriv, stand = A,
+                    useApply = FALSE)
+            erg <- E1/sum(diag(A %*% t(trafo)))
+            return(erg)
+        }
+
+        erg <- optim(as.numeric(A.start), bmin.fct, method = "Nelder-Mead",
+                    control = list(reltol = tol, maxit = 100*maxiter),
+                    L2deriv = L2deriv, Distr = Distr, trafo = trafo)
+
+        A <- matrix(erg$par, ncol = k, nrow = 1)
+        b <- 1/erg$value
+        stand(w) <- A
+
+        pr.fct <- function(x, L2, pr.sign=1){
+                  X <- evalRandVar(L2, as.matrix(x)) [,,1]
+                  Y <- as.numeric(A %*% X)
+                  return(as.numeric(pr.sign*Y>0))
+                  }
+        p.p   <- E(object = Distr, fun = pr.fct, L2 = L2deriv,
+                   useApply = FALSE, pr.sign =  1)
+        m.p   <- E(object = Distr, fun = pr.fct, L2 = L2deriv,
+                   useApply = FALSE, pr.sign = -1)
+
+
+        a <- -b * p.p/(p.p+m.p)
+        
+        clip(w) <- c(0,b)+a
+        weight(w) <- minbiasweight(w, neighbor = neighbor,
+                                           biastype = biastype,
+                                           normW = normtype)
+        return(list(A=A,b=b, w=w, a=a))
+    }
+

Modified: branches/robast-0.7/pkg/ROptEst/R/getInfCent.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/getInfCent.R	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/R/getInfCent.R	2009-08-20 22:18:16 UTC (rev 345)
@@ -46,11 +46,11 @@
         b <- clip[2]-clip[1]
         ### if(symm) return(b/2)
 
-        g.fct <- function(g, c0, D1){
+        g.fct <- function(g, c0){
             fct <- function(x){
                   Lx <- evalRandVar(L2deriv, as.matrix(x)) [,,1]
-                  D1 <- as.numeric(stand%*%Lx)
-                  pmin(pmax(g,D1),g+c0)
+                  Y <- as.numeric(stand%*%Lx)
+                  pmin(pmax(g,Y),g+c0)
                   }
             return(E(object = Distr, fun = fct, useApply = FALSE))
         }
@@ -58,7 +58,7 @@
         upper <- 0
 
         return(uniroot(g.fct, lower = lower, upper = upper, tol = tol.z,
-                    c0 = b, D1 = D1)$root)
+                    c0 = b)$root)
     })
 
 setMethod("getInfCent", signature(L2deriv = "RealRandVariable",

Modified: branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asBias.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asBias.R	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/R/getInfRobIC_asBias.R	2009-08-20 22:18:16 UTC (rev 345)
@@ -22,11 +22,15 @@
     })
 setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable", 
                                    risk = "asBias", 
-                                   neighbor = "ContNeighborhood"),
+                                   neighbor = "UncondNeighborhood"),
     function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
              L2derivDistrSymm, z.start, 
              A.start, Finfo, trafo, maxiter, tol, warn, verbose = FALSE, ...){
 
+        k <- ncol(trafo); p <- nrow(trafo)
+        if(is(neighbor,"TotalVarNeighborhood") && p>1)
+           stop("Not yet implemented.")
+
         normtype <- normtype(risk)
         if(is(normtype,"SelfNorm")){
                 warntxt <- paste(gettext(
@@ -59,20 +63,27 @@
            {QuadForm(normtype) <- PosSemDefSymmMatrix(FI); 
             normtype(risk) <- normtype}
 
-        comp <- .getComp(L2deriv, DistrSymm, L2derivSymm,
-             L2derivDistrSymm)
+        ## determine which entries must be computed
+        # by default everything
+        z.comp <- rep(TRUE,k)
+        A.comp <- matrix(rep(TRUE,k*k),nrow=k)
 
-        z.comp <- comp$"z.comp"
-        A.comp <- comp$"A.comp"
+        # otherwise if trafo == unitMatrix may use symmetry info
+        if(distrMod:::.isUnitMatrix(trafo)){
+            comp <- .getComp(L2deriv, DistrSymm, L2derivSymm, L2derivDistrSymm)
+            z.comp <- comp$"z.comp"
+            A.comp <- comp$"A.comp"
+        }
 
         return(minmaxBias(L2deriv = L2deriv, neighbor = neighbor,
                    biastype = biastype(risk), normtype = normtype(risk),
              Distr = Distr, z.start = z.start, A.start = A.start, 
-             z.comp = z.comp, A.comp = A.comp, trafo = trafo,
+             z.comp = z.comp, A.comp = A.comp, Finfo = Finfo, trafo = trafo,
              maxiter = maxiter, tol = tol, verbose = verbose))
     })
 
 
+
 ###############################################################################
 ## helper function minmaxBias
 ###############################################################################
@@ -153,12 +164,12 @@
                                    neighbor = "ContNeighborhood", 
                                    biastype = "BiasType"),
     function(L2deriv, neighbor, biastype, normtype, Distr, 
-             z.start, A.start,  z.comp, A.comp, trafo, maxiter,  tol,
+             z.start, A.start,  z.comp, A.comp, Finfo, trafo, maxiter,  tol,
              verbose = FALSE){
 
         DA.comp <- abs(trafo) %*% A.comp != 0
         eerg <- .LowerCaseMultivariate(L2deriv, neighbor, biastype,
-             normtype, Distr, trafo, z.start,
+             normtype, Distr, Finfo, trafo, z.start,
              A.start, z.comp = z.comp, A.comp = DA.comp, maxiter, tol,
              verbose = verbose)
         erg <- eerg$erg
@@ -182,6 +193,10 @@
         w <- eerg$w
         normtype <- eerg$normtype
 
+        if(verbose)
+           .checkPIC(L2deriv, neighbor, Distr, trafo, z, A, w, z.comp, A.comp)
+
+
         Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor, 
                        biastype = biastype, Distr = Distr, 
                        V.comp = A.comp, cent = a, 
@@ -205,6 +220,63 @@
                     w = w, biastype = biastype, normtype = normtype))
     })
 
+
+setMethod("minmaxBias", signature(L2deriv = "RealRandVariable",
+                                   neighbor = "TotalVarNeighborhood",
+                                   biastype = "BiasType"),
+    function(L2deriv, neighbor, biastype, normtype, Distr,
+             z.start, A.start,  z.comp, A.comp, Finfo, trafo, maxiter,  tol,
+             verbose = FALSE){
+
+        eerg <- .LowerCaseMultivariateTV(L2deriv = L2deriv,
+             neighbor = neighbor, biastype = biastype,
+             normtype = normtype, Distr = Distr, Finfo = Finfo, trafo = trafo,
+             A.start = A.start, maxiter = maxiter,
+             tol = tol, verbose = verbose)
+
+
+        p <- nrow(trafo)
+        k <- ncol(trafo)
+
+        A <- eerg$A
+        b <- eerg$b
+        w <- eerg$w
+        a <- eerg$a
+        z <- numeric(k)
+        d <- 0
+
+        # to be done:
+        # computation of 'd', in case 'L2derivDistr' not abs. cont.
+
+        if(verbose)
+           .checkPIC(L2deriv, neighbor, Distr, trafo, z, A, w,
+                     z.comp=rep(TRUE,k), A.comp=matrix(TRUE,k,k))
+
+
+        Cov <- getInfV(L2deriv = L2deriv, neighbor = neighbor,
+                       biastype = biastype, Distr = Distr,
+                       V.comp = matrix(TRUE), cent = numeric(k),
+                       stand = A, w = w)
+
+        std <- if(is(normtype,"QFNorm")) QuadForm(normtype) else diag(p)
+
+        info <- c("minimum asymptotic bias (lower case) solution")
+        trAsCov <- sum(diag(std%*%Cov))
+        r <- neighbor at radius
+        asMSE <- r^2 * b^2 + trAsCov
+        Risk <- list(asBias = list(value = b, biastype = biastype,
+                                   normtype = normtype,
+                                   neighbortype = class(neighbor)),
+                     asCov = Cov,
+                     trAsCov = list(value = trAsCov, normtype = normtype),
+                     asMSE = list(value = asMSE,
+                                  r = r,
+                                  at = neighbor))
+        return(list(A = A, a = a, b = b, d = d, risk = Risk, info = info,
+                    w = w, biastype = biastype, normtype = normtype))
+    })
+
+
 setMethod("minmaxBias", signature(L2deriv = "UnivariateDistribution", 
                                    neighbor = "ContNeighborhood", 
                                    biastype = "asymmetricBias"),

Modified: branches/robast-0.7/pkg/ROptEst/chm/00Index.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/00Index.html	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/00Index.html	2009-08-20 22:18:16 UTC (rev 345)
@@ -186,7 +186,7 @@
 <td>Functions to determine Lagrange multipliers</td></tr>
 <tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC</a></td>
 <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>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asBias,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,asCov,UncondNeighborhood-method</a></td>
 <td>Generic Function for the Computation of Optimally Robust ICs</td></tr>
@@ -312,6 +312,8 @@
 <td>Generic Function for the Computation of Bias-Optimally Robust ICs</td></tr>
 <tr><td width="25%"><a href="minmaxBias.html">minmaxBias,RealRandVariable,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,RealRandVariable,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,UnivariateDistribution,ContNeighborhood,asymmetricBias-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,BiasType-method</a></td>

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	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/ROptEst.toc	2009-08-20 22:18:16 UTC (rev 345)
@@ -290,7 +290,7 @@
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
-<param name="Name" value="getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method">
+<param name="Name" value="getInfRobIC,RealRandVariable,asBias,UncondNeighborhood-method">
 <param name="Local" value="getInfRobIC.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
@@ -522,6 +522,10 @@
 <param name="Local" value="minmaxBias.html">
 </OBJECT>
 <LI> <OBJECT type="text/sitemap">
+<param name="Name" value="minmaxBias,RealRandVariable,TotalVarNeighborhood,BiasType-method">
+<param name="Local" value="minmaxBias.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
 <param name="Name" value="minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
 <param name="Local" value="minmaxBias.html">
 </OBJECT>

Modified: branches/robast-0.7/pkg/ROptEst/chm/getInfCent.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/getInfCent.html	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/getInfCent.html	2009-08-20 22:18:16 UTC (rev 345)
@@ -102,7 +102,7 @@
 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>  
+object of class <code>RobWeight</code>; current weight</td></tr>
 </table>
 
 
@@ -165,7 +165,7 @@
 
 <h3>See Also</h3>
 
-<p><code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>, <code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code></p>
+<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) {

Modified: branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/getInfRobIC.html	2009-08-20 22:18:16 UTC (rev 345)
@@ -11,7 +11,7 @@
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-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,RealRandVariable,asBias,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method">
 <param name="keyword" value="R:   getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method">
@@ -56,7 +56,7 @@
                        risk, neighbor, symm, trafo,
                        maxiter, tol, warn, Finfo, verbose = FALSE, ...)
 
-## S4 method for signature 'RealRandVariable,asBias,ContNeighborhood':
+## S4 method for signature 'RealRandVariable,asBias,UncondNeighborhood':
 getInfRobIC(L2deriv, risk,
                        neighbor, Distr, DistrSymm, L2derivSymm,
                        L2derivDistrSymm, z.start, A.start, Finfo, trafo,
@@ -223,7 +223,7 @@
 </p>
 <p>
 <dt>L2deriv = "RealRandVariable", risk = "asBias", 
-neighbor = "ContNeighborhood"</dt><dd> 
+neighbor = "UncondNeighborhood"</dt><dd>
 computes the bias 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>
@@ -300,7 +300,7 @@
 
 <h3>See Also</h3>
 
-<p><code><a href="../../RobAStBase/html/InfRobModel-class.html">InfRobModel-class</a></code></p>
+<p><code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code></p>
 
 <script Language="JScript">
 function findlink(pkg, fn) {

Modified: branches/robast-0.7/pkg/ROptEst/chm/internals.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/internals.html	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/internals.html	2009-08-20 22:18:16 UTC (rev 345)
@@ -11,6 +11,8 @@
 <param name="keyword" value="R:   .getLowerSol">
 <param name="keyword" value="R:   .getLowUpB">
 <param name="keyword" value="R:   .checkPIC">
+<param name="keyword" value="R:   .LowerCaseMultivariate">
+<param name="keyword" value="R:   .LowerCaseMultivariateTV">
 <param name="keyword" value=" Internal / Helper functions of package ROptEst">
 </object>
 
@@ -55,6 +57,14 @@
 
 ### helper function to check whether (intermediate) results give a pIC
 .checkPIC(L2deriv, neighbor, Distr, trafo, z, A, w, z.comp, A.comp, ...)
+
+.LowerCaseMultivariatefunction(L2deriv, neighbor, biastype,
+             normtype, Distr, Finfo, trafo, z.start,
+             A.start, z.comp, A.comp, maxiter, tol, verbose = FALSE)
+
+.LowerCaseMultivariateTV(L2deriv, neighbor, biastype,
+             normtype, Distr, Finfo, trafo,
+             A.start,  maxiter, tol, verbose = FALSE)
 </pre>
 
 
@@ -170,6 +180,12 @@
 <code>.isVirginW</code> checks whether the (total variation) weight <code>w</code> in
 the argument has already been modified since creation (<code>TRUE</code> if not)
 <code>.checkPIC</code> checks whether (intermediate) results give a pIC
+<code>.LowerCaseMultivariatefunction</code> determines the Lagrange multipliers for
+the multivariate lower case solution for convex contamination
+by solving a corresponding dual problem (Rieder[94],p.199 eq.(18)).
+<code>.LowerCaseMultivariatefunctionTV</code> determines the Lagrange multipliers for
+the multivariate lower case solution for total variation in dimension <i>p=1</i>
+and <i>k&gt;1</i> by solving a corresponding dual problem (Rieder[94],p.205 eq.(58)).
 </p>
 
 
@@ -201,6 +217,20 @@
 <tr valign="top"><td><code>.checkPIC</code></td>
 <td>
 nothing is returned; precision values are issued.</td></tr>
+<tr valign="top"><td><code>.LowerCaseMultivariatefunction</code></td>
+<td>
+a list with elements
+<code>erg</code> the return value of the corresponding call to <code>optim</code>,
+<code>w</code> the corresponding weight (of class <code>HampelWeight</code>),
+<code>normtype</code> the norm &mdash;possibly modified,
+<code>z.comp</code> the indices of non-null entries in <code>z</code>.</td></tr>
+<tr valign="top"><td><code>.LowerCaseMultivariatefunctionTV</code></td>
+<td>
+a list with elements
+<code>A</code> the standardization matrix,
+<code>b</code> the minimax bias,
+<code>w</code> the corresponding weight (of class <code>BdStWeight</code>),
+<code>a</code> the corresponding infimum of the [p]IC.</td></tr>
 </table>
 </p>
 
@@ -211,5 +241,12 @@
 Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at itwm.fraunhofer.de">Peter.Ruckdeschel at itwm.fraunhofer.de</a>
 </p>
 
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+
 <hr><div align="center">[Package <em>ROptEst</em> version 0.7 <a href="00Index.html">Index</a>]</div>
 </body></html>

Modified: branches/robast-0.7/pkg/ROptEst/chm/minmaxBias.html
===================================================================
--- branches/robast-0.7/pkg/ROptEst/chm/minmaxBias.html	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/chm/minmaxBias.html	2009-08-20 22:18:16 UTC (rev 345)
@@ -1,10 +1,10 @@
 <html><head><title>Generic Function for the Computation of Bias-Optimally Robust ICs</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
 <link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
+</head><body>
 
-<table width="100%"><tr><td>minmaxBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<table width="100%"><tr><td>minmaxBias(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:   minmaxBias">
 <param name="keyword" value="R:   minmaxBias-methods">
 <param name="keyword" value="R:   minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
@@ -12,6 +12,7 @@
 <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">
+<param name="keyword" value="R:   minmaxBias,RealRandVariable,TotalVarNeighborhood,BiasType-method">
 <param name="keyword" value=" Generic Function for the Computation of Bias-Optimally Robust ICs">
 </object>
 
@@ -24,7 +25,7 @@
 <p>
 Generic function for the computation of bias-optimally robust ICs 
 in case of infinitesimal robust models. This function is 
-rarely called directly.
+rarely called directly. 
 </p>
 
 
@@ -33,31 +34,29 @@
 <pre>
 minmaxBias(L2deriv, neighbor, biastype, ...)
 
-## S4 method for signature 'UnivariateDistribution,
-##   ContNeighborhood, BiasType':
+## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType':
 minmaxBias(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
 
-## S4 method for signature 'UnivariateDistribution,
-##   ContNeighborhood, asymmetricBias':
+## S4 method for signature 'UnivariateDistribution,ContNeighborhood,asymmetricBias':
 minmaxBias(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
 
-## S4 method for signature 'UnivariateDistribution,
-##   ContNeighborhood, onesidedBias':
+## S4 method for signature 'UnivariateDistribution,ContNeighborhood,onesidedBias':
 minmaxBias(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
 
-## S4 method for signature 'UnivariateDistribution,
-##   TotalVarNeighborhood, BiasType':
+## S4 method for signature 'UnivariateDistribution,TotalVarNeighborhood,BiasType':
 minmaxBias(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
 
-## S4 method for signature 'RealRandVariable,
-##   ContNeighborhood, BiasType':
+## S4 method for signature 'RealRandVariable,ContNeighborhood,BiasType':
 minmaxBias(L2deriv, neighbor, biastype, normtype, Distr, 
-             z.start, A.start,  z.comp, A.comp, trafo, maxiter, tol, verbose = FALSE)
+             z.start, A.start,  z.comp, A.comp, Finfo, trafo, maxiter, tol, verbose = FALSE)
 
+## S4 method for signature 'RealRandVariable,TotalVarNeighborhood,BiasType':
+minmaxBias(L2deriv, neighbor, biastype, normtype, Distr,
+             z.start, A.start,  z.comp, A.comp, Finfo, trafo, maxiter, tol, verbose = FALSE)
 </pre>
 
 
@@ -66,95 +65,108 @@
 <table summary="R argblock">
 <tr valign="top"><td><code>L2deriv</code></td>
 <td>
-L2-derivative of some L2-differentiable family 
+ 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>
+ 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>"BiasType"</code>. </td></tr>
 <tr valign="top"><td><code>normtype</code></td>
 <td>
-object of class <code>"NormType"</code>. </td></tr>
+ object of class <code>"NormType"</code>. </td></tr>
 <tr valign="top"><td><code>...</code></td>
 <td>
-additional parameters. </td></tr>
+ additional parameters. </td></tr>
 <tr valign="top"><td><code>Distr</code></td>
 <td>
-object of class <code>"Distribution"</code>. </td></tr>
+ object of class <code>"Distribution"</code>. </td></tr>
 <tr valign="top"><td><code>symm</code></td>
 <td>
-logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+ logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
 <tr valign="top"><td><code>z.start</code></td>
 <td>
-initial value for the centering constant. </td></tr>
+ initial value for the centering constant. </td></tr>
 <tr valign="top"><td><code>A.start</code></td>
 <td>
-initial value for the standardizing matrix. </td></tr>
+ initial value for the standardizing matrix. </td></tr>
 <tr valign="top"><td><code>z.comp</code></td>
 <td>
-<code>logical</code> indicator which indices need to be computed and which are 0 due to symmetry. </td></tr>
+ <code>logical</code> indicator which indices need to be computed and which are 0 due to symmetry. </td></tr>
 <tr valign="top"><td><code>A.comp</code></td>
 <td>
-<code>matrix</code> of <code>logical</code> indicator which indices need to be computed and which are 0 due to symmetry.</td></tr>
+ <code>matrix</code> of <code>logical</code> indicator which indices need to be computed and which are 0 due to symmetry.</td></tr>
 <tr valign="top"><td><code>trafo</code></td>
 <td>
-matrix: transformation of the parameter. </td></tr>
+ matrix: transformation of the parameter. </td></tr>
 <tr valign="top"><td><code>maxiter</code></td>
 <td>
-the maximum number of iterations. </td></tr>
+ the maximum number of iterations. </td></tr>
 <tr valign="top"><td><code>tol</code></td>
 <td>
-the desired accuracy (convergence tolerance).</td></tr>
+ the desired accuracy (convergence tolerance).</td></tr>
 <tr valign="top"><td><code>warn</code></td>
 <td>
-logical: print warnings. </td></tr>
+ logical: print warnings. </td></tr>
 <tr valign="top"><td><code>Finfo</code></td>
 <td>
-Fisher information matrix. </td></tr>
+ Fisher information matrix. </td></tr>
 <tr valign="top"><td><code>verbose</code></td>
 <td>
-logical: if <code>TRUE</code>, some messages are printed </td></tr>
+ logical: if <code>TRUE</code>, some messages are printed </td></tr>
 </table>
 
+
 <h3>Value</h3>
 
-<p>
-The bias-optimally robust IC is computed.</p>
+<p>The bias-optimally robust IC is computed.</p>
 
+
 <h3>Methods</h3>
 
+<p>
+
 <dl>
 <dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", 
-biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable 
+biastype = "BiasType"</dt><dd> 
+computes the bias optimal influence curve for symmetric bias for L2 differentiable 
 parametric families with unknown one-dimensional parameter. </dd>
-
-
+</p>
+<p>
 <dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", 
-biastype = "asymmetricBias"</dt><dd>computes the bias optimal influence curve for asymmetric bias for L2 differentiable 
+biastype = "asymmetricBias"</dt><dd> 
+computes the bias optimal influence curve for asymmetric bias for L2 differentiable 
 parametric families with unknown one-dimensional parameter. </dd>
-
-
+</p>
+<p>
 <dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", 
-biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable 
+biastype = "BiasType"</dt><dd> 
+computes the bias optimal influence curve for symmetric bias for L2 differentiable 
 parametric families with unknown one-dimensional parameter. </dd>
-
-
+</p>
+<p>
 <dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", 
-biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable 
+biastype = "BiasType"</dt><dd> 
+computes the bias optimal influence curve for symmetric bias for L2 differentiable 
 parametric families with unknown <i>k</i>-dimensional parameter 
 (<i>k &gt; 1</i>) where the underlying distribution is univariate. </dd>
-
+</p>
 <p>
+<dt>L2deriv = "RealRandVariable", neighbor = "TotalNeighborhood",
+biastype = "BiasType"</dt><dd>
+computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families in a setting where we are interested in a <i>p=1</i>
+dimensional aspect of an unknown <i>k</i>-dimensional parameter
+(<i>k &gt; 1</i>) where the underlying distribution is univariate. </dd>
 </dl>
+</p>
 
+
 <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 itwm.fraunhofer.de">Peter.Ruckdeschel at itwm.fraunhofer.de</a>
-</p>
+<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 itwm.fraunhofer.de">Peter.Ruckdeschel at itwm.fraunhofer.de</a></p>
 
 
 <h3>References</h3>
@@ -177,9 +189,7 @@
 
 <h3>See Also</h3>
 
-<p>
-<code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
-</p>
+<p><code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code></p>
 
 <script Language="JScript">
 function findlink(pkg, fn) {
@@ -191,7 +201,5 @@
 }
 </script>
 
-
 <hr><div align="center">[Package <em>ROptEst</em> version 0.7 <a href="00Index.html">Index</a>]</div>
-
 </body></html>

Modified: branches/robast-0.7/pkg/ROptEst/inst/scripts/NormalLocationScaleModel.R
===================================================================
--- branches/robast-0.7/pkg/ROptEst/inst/scripts/NormalLocationScaleModel.R	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/inst/scripts/NormalLocationScaleModel.R	2009-08-20 22:18:16 UTC (rev 345)
@@ -125,6 +125,11 @@
 plot(IC.traf.CV.MSE)
 checkIC(IC.traf.CV.MSE)
 
+### lower case solution *=c
+IC.traf.CV.BIAS <- optIC(model = N1R.traf, risk = asBias(),verbose=TRUE)
+plot(IC.traf.CV.BIAS)
+checkIC(IC.traf.CV.BIAS)
+
 ### Hampel solution *=v
 IC.traf.TV.H <- optIC(model = N2R.traf, risk = asHampel(bound = 6),
                       verbose=TRUE, checkBounds=FALSE)
@@ -136,7 +141,12 @@
 plot(IC.traf.TV.MSE)
 checkIC(IC.traf.TV.MSE)
 
+### lower case solution *=v
+IC.traf.TV.BIAS <- optIC(model = N2R.traf, risk = asBias(),verbose=TRUE)
+plot(IC.traf.TV.BIAS)
+checkIC(IC.traf.TV.BIAS)
 
+
 ###############################################################################
 ## one-step estimation
 ###############################################################################

Modified: branches/robast-0.7/pkg/ROptEst/man/getInfCent.Rd
===================================================================
--- branches/robast-0.7/pkg/ROptEst/man/getInfCent.Rd	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/man/getInfCent.Rd	2009-08-20 22:18:16 UTC (rev 345)
@@ -51,7 +51,7 @@
   \item{Distr}{object of class \code{Distribution}. }
   \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}  
+  \item{w}{object of class \code{RobWeight}; current weight}
 }
 %\details{}
 \value{The optimal centering constant is computed.}

Modified: branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd
===================================================================
--- branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd	2009-08-20 19:15:56 UTC (rev 344)
+++ branches/robast-0.7/pkg/ROptEst/man/getInfRobIC.Rd	2009-08-20 22:18:16 UTC (rev 345)
@@ -5,7 +5,7 @@
 \alias{getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method}
 \alias{getInfRobIC,RealRandVariable,asCov,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method}
-\alias{getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method}
+\alias{getInfRobIC,RealRandVariable,asBias,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method}
 \alias{getInfRobIC,RealRandVariable,asHampel,UncondNeighborhood-method}
 \alias{getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method}
@@ -35,7 +35,7 @@
                        risk, neighbor, symm, trafo,
                        maxiter, tol, warn, Finfo, verbose = FALSE, ...)
 
-\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk,
+\S4method{getInfRobIC}{RealRandVariable,asBias,UncondNeighborhood}(L2deriv, risk,
                        neighbor, Distr, DistrSymm, L2derivSymm,
                        L2derivDistrSymm, z.start, A.start, Finfo, trafo,
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/robast -r 345


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