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) .


Reference manual

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1.4 by Riko Kelter, a year ago

Browse source code at https://github.com/cran/bayest

Authors: Riko Kelter

Documentation:   PDF Manual  

GPL-3 license

Imports MCMCpack

Suggests coda, MASS

See at CRAN