[Robast-commits] r1272 - in pkg/ROptEstOld: . inst man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Feb 4 13:09:43 CET 2024
Author: stamats
Date: 2024-02-04 13:09:42 +0100 (Sun, 04 Feb 2024)
New Revision: 1272
Modified:
pkg/ROptEstOld/DESCRIPTION
pkg/ROptEstOld/inst/NEWS
pkg/ROptEstOld/man/getIneffDiff.Rd
pkg/ROptEstOld/man/leastFavorableRadius.Rd
pkg/ROptEstOld/man/radiusMinimaxIC.Rd
Log:
update of references
Modified: pkg/ROptEstOld/DESCRIPTION
===================================================================
--- pkg/ROptEstOld/DESCRIPTION 2024-02-04 08:41:04 UTC (rev 1271)
+++ pkg/ROptEstOld/DESCRIPTION 2024-02-04 12:09:42 UTC (rev 1272)
@@ -1,5 +1,5 @@
Package: ROptEstOld
-Version: 1.2.1
+Version: 1.2.2
Date: 2024-02-04
Title: Optimally Robust Estimation - Old Version
Description: Optimally robust estimation using S4 classes and methods. Old version still
Modified: pkg/ROptEstOld/inst/NEWS
===================================================================
--- pkg/ROptEstOld/inst/NEWS 2024-02-04 08:41:04 UTC (rev 1271)
+++ pkg/ROptEstOld/inst/NEWS 2024-02-04 12:09:42 UTC (rev 1272)
@@ -14,6 +14,7 @@
under the hood
+ now specified that we want to use distr::solve
+ removed latin1 encoding
++ update of some references and links
#######################################
version 1.1
Modified: pkg/ROptEstOld/man/getIneffDiff.Rd
===================================================================
--- pkg/ROptEstOld/man/getIneffDiff.Rd 2024-02-04 08:41:04 UTC (rev 1271)
+++ pkg/ROptEstOld/man/getIneffDiff.Rd 2024-02-04 12:09:42 UTC (rev 1272)
@@ -1,60 +1,63 @@
-\name{getIneffDiff}
-\alias{getIneffDiff}
-\alias{getIneffDiff-methods}
-\alias{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE-method}
-
-\title{Generic Function for the Computation of Inefficiency Differences}
-\description{
- Generic function for the computation of inefficiency differencies.
- This function is rarely called directly. It is used to compute
- the radius minimax IC and the least favorable radius.
-}
-\usage{
-getIneffDiff(radius, L2Fam, neighbor, risk, ...)
-
-\S4method{getIneffDiff}{numeric,L2ParamFamily,UncondNeighborhood,asMSE}(radius, L2Fam, neighbor, risk, loRad, upRad,
- loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
-}
-\arguments{
- \item{radius}{ neighborhood radius. }
- \item{L2Fam}{ L2-differentiable family of probability measures. }
- \item{neighbor}{ object of class \code{"Neighborhood"}. }
- \item{risk}{ object of class \code{"RiskType"}. }
- \item{\dots}{ additional parameters }
- \item{loRad}{ the lower end point of the interval to be searched. }
- \item{upRad}{ the upper end point of the interval to be searched. }
- \item{loRisk}{ the risk at the lower end point of the interval. }
- \item{upRisk}{ the risk at the upper end point of the interval. }
- \item{z.start}{ initial value for the centering constant. }
- \item{A.start}{ initial value for the standardizing matrix. }
- \item{upper.b}{ upper bound for the optimal clipping bound. }
- \item{MaxIter}{ the maximum number of iterations }
- \item{eps}{ the desired accuracy (convergence tolerance).}
- \item{warn}{ logical: print warnings. }
-}
-%\details{}
-\value{The inefficieny difference between the left and
- the right margin of a given radius interval is computed.
-}
-\section{Methods}{
-\describe{
- \item{radius = "numeric", L2Fam = "L2ParamFamily",
- neighbor = "UncondNeighborhood", risk = "asMSE":}{
- computes difference of asymptotic MSE--inefficiency for
- the boundaries of a given radius interval.}
-}}
-\references{
- Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
- the Radius. Submitted. Appeared as discussion paper Nr. 81.
- SFB 373 (Quantification and Simulation of Economic Processes),
- Humboldt University, Berlin; also available under
- \url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{radiusMinimaxIC}}, \code{\link{leastFavorableRadius}}}
-%\examples{}
-\keyword{robust}
+\name{getIneffDiff}
+\alias{getIneffDiff}
+\alias{getIneffDiff-methods}
+\alias{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE-method}
+
+\title{Generic Function for the Computation of Inefficiency Differences}
+\description{
+ Generic function for the computation of inefficiency differencies.
+ This function is rarely called directly. It is used to compute
+ the radius minimax IC and the least favorable radius.
+}
+\usage{
+getIneffDiff(radius, L2Fam, neighbor, risk, ...)
+
+\S4method{getIneffDiff}{numeric,L2ParamFamily,UncondNeighborhood,asMSE}(radius, L2Fam, neighbor, risk, loRad, upRad,
+ loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
+}
+\arguments{
+ \item{radius}{ neighborhood radius. }
+ \item{L2Fam}{ L2-differentiable family of probability measures. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{risk}{ object of class \code{"RiskType"}. }
+ \item{\dots}{ additional parameters }
+ \item{loRad}{ the lower end point of the interval to be searched. }
+ \item{upRad}{ the upper end point of the interval to be searched. }
+ \item{loRisk}{ the risk at the lower end point of the interval. }
+ \item{upRisk}{ the risk at the upper end point of the interval. }
+ \item{z.start}{ initial value for the centering constant. }
+ \item{A.start}{ initial value for the standardizing matrix. }
+ \item{upper.b}{ upper bound for the optimal clipping bound. }
+ \item{MaxIter}{ the maximum number of iterations }
+ \item{eps}{ the desired accuracy (convergence tolerance).}
+ \item{warn}{ logical: print warnings. }
+}
+%\details{}
+\value{The inefficieny difference between the left and
+ the right margin of a given radius interval is computed.
+}
+\section{Methods}{
+\describe{
+ \item{radius = "numeric", L2Fam = "L2ParamFamily",
+ neighbor = "UncondNeighborhood", risk = "asMSE":}{
+ computes difference of asymptotic MSE--inefficiency for
+ the boundaries of a given radius interval.}
+}}
+\references{
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+ the Radius. Statistical Methods and Applications, \emph{17}(1) 13-40.
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+ the Radius. Submitted. Appeared as discussion paper Nr. 81.
+ SFB 373 (Quantification and Simulation of Economic Processes),
+ Humboldt University, Berlin; also available under
+ \doi{10.18452/3638}
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+%\note{}
+\seealso{\code{\link{radiusMinimaxIC}}, \code{\link{leastFavorableRadius}}}
+%\examples{}
+\keyword{robust}
Modified: pkg/ROptEstOld/man/leastFavorableRadius.Rd
===================================================================
--- pkg/ROptEstOld/man/leastFavorableRadius.Rd 2024-02-04 08:41:04 UTC (rev 1271)
+++ pkg/ROptEstOld/man/leastFavorableRadius.Rd 2024-02-04 12:09:42 UTC (rev 1272)
@@ -1,61 +1,67 @@
-\name{leastFavorableRadius}
-\alias{leastFavorableRadius}
-\alias{leastFavorableRadius-methods}
-\alias{leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method}
-
-\title{Generic Function for the Computation of Least Favorable Radii}
-\description{
- Generic function for the computation of least favorable radii.
-}
-\usage{
-leastFavorableRadius(L2Fam, neighbor, risk, ...)
-
-\S4method{leastFavorableRadius}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk, rho, upRad = 1,
- z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
- tol = .Machine$double.eps^0.4, warn = FALSE)
-}
-\arguments{
- \item{L2Fam}{ L2-differentiable family of probability measures. }
- \item{neighbor}{ object of class \code{"Neighborhood"}. }
- \item{risk}{ object of class \code{"RiskType"}. }
- \item{\dots}{ additional parameters }
- \item{upRad}{ the upper end point of the radius interval to be searched. }
- \item{rho}{ The considered radius interval is: \eqn{[r \rho, r/\rho]}{[r*rho, r/rho]}
- with \eqn{\rho\in(0,1)}{0 < rho < 1}. }
- \item{z.start}{ initial value for the centering constant. }
- \item{A.start}{ initial value for the standardizing matrix. }
- \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 least favorable radius and the corresponding inefficiency
- are computed.
-}
-\section{Methods}{
-\describe{
- \item{L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood",
- risk = "asGRisk"}{ computation of the least favorable radius. }
-}}
-\references{
- Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
- the Radius. Submitted. Appeared as discussion paper Nr. 81.
- SFB 373 (Quantification and Simulation of Economic Processes),
- Humboldt University, Berlin; also available under
- \url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{radiusMinimaxIC}}}
-\examples{
-N <- NormLocationFamily(mean=0, sd=1)
-leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
- risk=asMSE(), rho=0.5)
-}
-\concept{least favorable radius}
-\keyword{robust}
+\name{leastFavorableRadius}
+\alias{leastFavorableRadius}
+\alias{leastFavorableRadius-methods}
+\alias{leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method}
+
+\title{Generic Function for the Computation of Least Favorable Radii}
+\description{
+ Generic function for the computation of least favorable radii.
+}
+\usage{
+leastFavorableRadius(L2Fam, neighbor, risk, ...)
+
+\S4method{leastFavorableRadius}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk, rho, upRad = 1,
+ z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
+ tol = .Machine$double.eps^0.4, warn = FALSE)
+}
+\arguments{
+ \item{L2Fam}{ L2-differentiable family of probability measures. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{risk}{ object of class \code{"RiskType"}. }
+ \item{\dots}{ additional parameters }
+ \item{upRad}{ the upper end point of the radius interval to be searched. }
+ \item{rho}{ The considered radius interval is: \eqn{[r \rho, r/\rho]}{[r*rho, r/rho]}
+ with \eqn{\rho\in(0,1)}{0 < rho < 1}. }
+ \item{z.start}{ initial value for the centering constant. }
+ \item{A.start}{ initial value for the standardizing matrix. }
+ \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 least favorable radius and the corresponding inefficiency
+ are computed.
+}
+\section{Methods}{
+\describe{
+ \item{L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood",
+ risk = "asGRisk"}{ computation of the least favorable radius. }
+}}
+\references{
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+ the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+ the Radius. Submitted. Appeared as discussion paper Nr. 81.
+ SFB 373 (Quantification and Simulation of Economic Processes),
+ Humboldt University, Berlin; also available under
+ \doi{10.18452/3638}
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+%\note{}
+\seealso{\code{\link{radiusMinimaxIC}}}
+\examples{
+N <- NormLocationFamily(mean=0, sd=1)
+leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+}
+\concept{least favorable radius}
+\keyword{robust}
Modified: pkg/ROptEstOld/man/radiusMinimaxIC.Rd
===================================================================
--- pkg/ROptEstOld/man/radiusMinimaxIC.Rd 2024-02-04 08:41:04 UTC (rev 1271)
+++ pkg/ROptEstOld/man/radiusMinimaxIC.Rd 2024-02-04 12:09:42 UTC (rev 1272)
@@ -1,58 +1,61 @@
-\name{radiusMinimaxIC}
-\alias{radiusMinimaxIC}
-\alias{radiusMinimaxIC-methods}
-\alias{radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method}
-
-\title{Generic function for the computation of the radius minimax IC}
-\description{
- Generic function for the computation of the radius minimax IC.
-}
-\usage{
-radiusMinimaxIC(L2Fam, neighbor, risk, ...)
-
-\S4method{radiusMinimaxIC}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk,
- loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
- maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
-}
-\arguments{
- \item{L2Fam}{ L2-differentiable family of probability measures. }
- \item{neighbor}{ object of class \code{"Neighborhood"}. }
- \item{risk}{ object of class \code{"RiskType"}. }
- \item{\dots}{ additional parameters. }
- \item{loRad}{ the lower end point of the interval to be searched. }
- \item{upRad}{ the upper end point of the interval to be searched. }
- \item{z.start}{ initial value for the centering constant. }
- \item{A.start}{ initial value for the standardizing matrix. }
- \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 radius minimax IC is computed.}
-\section{Methods}{
-\describe{
- \item{L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk":}{
- computation of the radius minimax IC for an L2 differentiable parametric family. }
-}}
-\references{
- Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
- the Radius. Submitted. Appeared as discussion paper Nr. 81.
- SFB 373 (Quantification and Simulation of Economic Processes),
- Humboldt University, Berlin; also available under
- \url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{radiusMinimaxIC}}}
-\examples{
-N <- NormLocationFamily(mean=0, sd=1)
-radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
- risk=asMSE(), loRad=0.1, upRad=0.5)
-}
-\concept{radius minimax influence curve}
-\concept{influence curve}
-\keyword{robust}
+\name{radiusMinimaxIC}
+\alias{radiusMinimaxIC}
+\alias{radiusMinimaxIC-methods}
+\alias{radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method}
+
+\title{Generic function for the computation of the radius minimax IC}
+\description{
+ Generic function for the computation of the radius minimax IC.
+}
+\usage{
+radiusMinimaxIC(L2Fam, neighbor, risk, ...)
+
+\S4method{radiusMinimaxIC}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk,
+ loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
+ maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
+}
+\arguments{
+ \item{L2Fam}{ L2-differentiable family of probability measures. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{risk}{ object of class \code{"RiskType"}. }
+ \item{\dots}{ additional parameters. }
+ \item{loRad}{ the lower end point of the interval to be searched. }
+ \item{upRad}{ the upper end point of the interval to be searched. }
+ \item{z.start}{ initial value for the centering constant. }
+ \item{A.start}{ initial value for the standardizing matrix. }
+ \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 radius minimax IC is computed.}
+\section{Methods}{
+\describe{
+ \item{L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk":}{
+ computation of the radius minimax IC for an L2 differentiable parametric family. }
+}}
+\references{
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+ the Radius. Statistical Methods and Applications, \emph{17}(1) 13-40.
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+ the Radius. Appeared as discussion paper Nr. 81.
+ SFB 373 (Quantification and Simulation of Economic Processes),
+ Humboldt University, Berlin; also available under
+ \doi{10.18452/3638}
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+%\note{}
+\seealso{\code{\link{radiusMinimaxIC}}}
+\examples{
+N <- NormLocationFamily(mean=0, sd=1)
+radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+}
+\concept{radius minimax influence curve}
+\concept{influence curve}
+\keyword{robust}
More information about the Robast-commits
mailing list