bayest: Bayesian t-Test

Provides an Markov-Chain-Monte-Carlo algorithm for Bayesian t-tests on the effect size. The underlying Gibbs sampler is based on a two-component Gaussian mixture and approximates the posterior distributions of the effect size, the difference of means and difference of standard deviations. A posterior analysis of the effect size via the region of practical equivalence is provided, too. For more details about the Gibbs sampler see Kelter (2019) <arXiv:1906.07524>.

Version: 1.0
Suggests: MCMCpack, coda, MASS
Published: 2019-08-02
Author: Riko Kelter
Maintainer: Riko Kelter <riko.kelter at uni-siegen.de>
License: GPL-2
NeedsCompilation: no
CRAN checks: bayest results

Downloads:

Reference manual: bayest.pdf
Package source: bayest_1.0.tar.gz
Windows binaries: r-devel: bayest_1.0.zip, r-release: bayest_1.0.zip, r-oldrel: bayest_1.0.zip
OS X binaries: r-release: bayest_1.0.tgz, r-oldrel: bayest_1.0.tgz

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