Package: bayest 1.5
bayest: 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) <arxiv:1906.07524>.
Authors:
bayest_1.5.tar.gz
bayest_1.5.zip(r-4.7)bayest_1.5.zip(r-4.6)bayest_1.5.zip(r-4.5)
bayest_1.5.tgz(r-4.6-any)bayest_1.5.tgz(r-4.5-any)
bayest_1.5.tar.gz(r-4.7-any)bayest_1.5.tar.gz(r-4.6-any)
bayest_1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bayest/json (API)
| # Install 'bayest' in R: |
| install.packages('bayest', repos = c('https://riko-k.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:45fd89f2cc. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 119 | ||
| source / vignettes | OK | 139 | ||
| linux-release-x86_64 | OK | 101 | ||
| macos-release-arm64 | OK | 70 | ||
| macos-oldrel-arm64 | OK | 74 | ||
| windows-devel | OK | 115 | ||
| windows-release | OK | 59 | ||
| windows-oldrel | OK | 110 | ||
| wasm-release | OK | 95 |
Exports:bayes.t.test
Dependencies:codalatticeMASSMatrixMatrixModelsmcmcMCMCpackquantregSparseMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Effect Size Targeted Bayesian Two-Sample t-Tests via Markov Chain Monte Carlo in Gaussian Mixture Models | bayest-package bayest |
| bayesttest | bayes.t.test |
