Ultimixt: Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior

A generic reference Bayesian analysis of unidimensional mixture distributions obtained by a location-scale parameterisation of the model is implemented. The including functions simulate and summarize posterior samples for location-scale mixture models using a weakly informative prior. There is no need to define priors for scale-location parameters except two hyperparameters in which are associated with a Dirichlet prior for weights and a simplex.

Version: 2.1
Depends: coda, gtools, graphics, grDevices, stats
Published: 2017-03-09
Author: Kaniav Kamary, Kate Lee
Maintainer: Kaniav Kamary <kamary at ceremade.dauphine.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
CRAN checks: Ultimixt results

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Reference manual: Ultimixt.pdf
Package source: Ultimixt_2.1.tar.gz
Windows binaries: r-devel: Ultimixt_2.1.zip, r-release: Ultimixt_2.1.zip, r-oldrel: Ultimixt_2.1.zip
OS X El Capitan binaries: r-release: Ultimixt_2.1.tgz
OS X Mavericks binaries: r-oldrel: Ultimixt_2.1.tgz
Old sources: Ultimixt archive

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