bayest-package {bayest}R Documentation

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

Description

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>.

Details

Package for conducting Bayesian two-sample t-tests based on a two-component Gaussian mixture model via Gibbs sampling.

Package: bayest
Type: Package
Title: Effect Size Targeted Bayesian Two-Sample t-Tests via Markov Chain Monte Carlo in Gaussian Mixture Models
Version: 1.4
Date: 2020-05-30
Author: Riko Kelter
Maintainer: Riko Kelter <riko.kelter@uni-siegen.de>
Description: 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>.
Imports: MCMCpack
Suggests: coda, MASS
License: GPL-3

Index of help topics:

bayes.t.test            bayesttest
bayest-package          Effect Size Targeted Bayesian Two-Sample
                        t-Tests via Markov Chain Monte Carlo in
                        Gaussian Mixture Models

Author(s)

Riko Kelter

Maintainer: Riko Kelter <riko.kelter@uni-siegen.de>

References

For a detailed explanation of the underlying Gibbs sampler see: https://arxiv.org/abs/1906.07524v1


[Package bayest version 1.4 Index]