luck: Generalized iLUCK models

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]
MaintainerGero Walter <Gero.Walter@stat.uni-muenchen.de>
LicenseArtistic-2.0
Version0.9
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("luck", repos="http://R-Forge.R-project.org")

Try the luck package in your browser

Any scripts or data that you put into this service are public.

luck documentation built on May 2, 2019, 4:43 p.m.