bayest: Effect Size Targeted Bayesian Two-Sample t-Tests via Markov Chain Monte Carlo in Gaussian Mixture Models

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: 1.4
Imports: MCMCpack
Suggests: coda, MASS
Published: 2020-05-31
Author: Riko Kelter
Maintainer: Riko Kelter <riko.kelter at>
License: GPL-3
NeedsCompilation: no
CRAN checks: bayest results


Reference manual: bayest.pdf
Package source: bayest_1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bayest_1.4.tgz, r-oldrel: bayest_1.4.tgz
Old sources: bayest archive


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