| 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: | 1.5 |
| Date: | 2024-04-05 |
| 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