imprProbEst: Minimum distance estimation in an imprecise probability model

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.

Version: 1.0.1
Depends: R (≥ 2.7.0), inline, lpSolve
Published: 2010-05-07
Author: Robert Hable
Maintainer: Robert Hable <Robert.Hable at uni-bayreuth.de>
License: LGPL-3
NeedsCompilation: no
Citation: imprProbEst citation info
CRAN checks: imprProbEst results

Downloads:

Reference manual: imprProbEst.pdf
Package source: imprProbEst_1.0.1.tar.gz
OS X binary: imprProbEst_1.0.1.tgz
Windows binary: imprProbEst_1.0.1.zip
Old sources: imprProbEst archive