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.
Author  Robert Hable 
Date of publication  20100507 16:10:30 
Maintainer  Robert Hable <Robert.Hable@unibayreuth.de> 
License  LGPL3 
Version  1.0.1 
Package repository  View on CRAN 
Installation  Install the latest version of this package by entering the following in R:





All man pages Function index File listing
Man pages  

ArgMinDist: A Minimum Distance Estimation  
imprProbEstpackage: Minimum distance estimation in an imprecise probability model 
Functions 

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