imprProbEst: Minimum distance estimation in an imprecise probability model
Version 1.0.1

A minimum distance estimator is calculated for an imprecise probability model. The imprecise probability model consists of upper coherent previsions whose credal sets are given by a finite number of constraints on the expectations. The parameter set is finite. The estimator chooses that parameter such that the empirical measure lies next to the corresponding credal set with respect to the total variation norm.

AuthorRobert Hable
Date of publication2010-05-07 16:10:30
MaintainerRobert Hable <Robert.Hable@uni-bayreuth.de>
LicenseLGPL-3
Version1.0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("imprProbEst")

Getting started

Package overview

Popular man pages

ArgMinDist: A Minimum Distance Estimation
imprProbEst-package: Minimum distance estimation in an imprecise probability model
See all...

All man pages Function index File listing

Man pages

ArgMinDist: A Minimum Distance Estimation
imprProbEst-package: Minimum distance estimation in an imprecise probability model

Functions

Files

DESCRIPTION
inst
inst/CITATION
man
man/ArgMinDist.Rd
man/imprProbEst-package.Rd
NAMESPACE
R
R/ArgMinDist.R
R/BuildBounds.R
R/BuildBounds1.R
R/BuildBounds2.R
R/BuildMatrix.R
R/BuildMatrix1.R
R/BuildMatrix2.R
R/BuildOptVec.R
R/BuildSupportingNodes.R
R/DiscretizeImpreciseModel.R
R/FctReducedNodevalues.R
R/fevaluation.R
R/TotalVar.R
imprProbEst documentation built on May 19, 2017, 1:32 p.m.

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