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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) <doi:10.48550/arXiv.1906.07524>.
| Version: | 1.5 |
| Imports: | MCMCpack |
| Suggests: | coda, MASS |
| Published: | 2024-04-05 |
| Author: | Riko Kelter |
| Maintainer: | Riko Kelter <riko.kelter at uni-siegen.de> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | bayest results |
| Reference manual: | bayest.pdf |
| Package source: | bayest_1.5.tar.gz |
| Windows binaries: | r-devel: bayest_1.5.zip, r-release: bayest_1.5.zip, r-oldrel: bayest_1.5.zip |
| macOS binaries: | r-release (arm64): bayest_1.5.tgz, r-oldrel (arm64): bayest_1.5.tgz, r-release (x86_64): bayest_1.5.tgz, r-oldrel (x86_64): bayest_1.5.tgz |
| Old sources: | bayest archive |
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