luck: Generalized iLUCK models
Version 0.9

Generalized iLUCK-models are a way to define sets of priors based on conjugate priors, with the property that the set of posteriors, obtained by updating each prior in the set by Bayes' rule, is still easy to handle. Generalized iLUCK-models belong to the domain of imprecise probability (or interval probability models), allow to include non-stochastic uncertainty ('ambiguity') in Bayesian analysis, and lead to reasonable inferences in case of prior-data conflict.

Package details

AuthorGero Walter [aut, cre], Norbert Krautenbacher [aut]
Date of publication2013-08-27 15:53:15
MaintainerGero Walter <[email protected]>
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("luck", repos="")

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luck documentation built on May 31, 2017, 1:52 a.m.