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bayest  

Effect Size Targeted Bayesian Two-Sample t-Tests via Markov Chain Monte Carlo in Gaussian Mixture Models
View on CRAN: Click here


Download and install bayest package within the R console
Install from CRAN:
install.packages("bayest")

Install from Github:
library("remotes")
install_github("cran/bayest")

Install by package version:
library("remotes")
install_version("bayest", "1.5")



Attach the package and use:
library("bayest")
Maintained by
Riko Kelter
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-02
Latest Update: 2020-05-31
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) .
How to cite:
Riko Kelter (2019). bayest: Effect Size Targeted Bayesian Two-Sample t-Tests via Markov Chain Monte Carlo in Gaussian Mixture Models. R package version 1.5, https://cran.r-project.org/web/packages/bayest. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2019-08-02 13:10), 1.1 (2019-12-13 13:00), 1.2 (2020-05-05 13:00), 1.3 (2020-05-27 10:10), 1.4 (2020-05-31 03:40)
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Complete documentation for bayest
Functions, R codes and Examples using the bayest R package
Some associated functions: bayes.t.test . bayest-package . 
Some associated R codes: bayest.R .  Full bayest package functions and examples
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