bayest (1.0)

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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) .

Maintainer: Riko Kelter
Author(s): Riko Kelter

License: GPL-2

Uses: MCMCpack, coda, MASS

Released 4 months ago.



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