imprProbEst 1.0.1

Minimum distance estimation in an imprecise probability model

Released May 7, 2010 by Robert Hable

This package can be loaded by Renjin but all tests failed.


inline 0.3.15 lpSolve 5.6.13

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.



This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

    <name>bedatadriven public repo</name>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:


Test Results

This package was last tested against Renjin 0.9.2689 on Aug 27, 2018.



View GitHub Mirror

Release History