Skip to content

The Bayesian playground. A package for learning Bayes factors

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md
Notifications You must be signed in to change notification settings

ljcolling/bayesplay

 
 

Repository files navigation

bayesplay: The Bayesian playground

R-CMD-check CRAN downloads codecov

The goal of bayesplay is to provide an interface for calculating Bayes factors for simple models. It does this in a way that makes the calculations more transparent and it is therefore useful as a teaching tools.

Installation

bayesplay is now on CRAN. You can install it with:

install.packages("bayesplay")

Or if you want to live on the edge, you can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("bayesplay/bayesplay")

Basic usage

The bayesplay package comes with three basic functions for computing Bayes factors.

  1. The likelihood() function for specifying likelihoods

  2. The prior() function for specifying priors

  3. And the integral() function

Currently the following distributions are supported for likelihoods and priors

Priors

  1. Normal distribution (normal)

  2. Uniform distribution (uniform)

  3. Scaled and shifted t distribution (student_t)

  4. Cauchy distributions (cauchy)

  5. Beta distribution (beta)

Likelihood

  1. Normal distribution (normal)

  2. Scaled and shifted t distribution (student_t)

  3. Binomial distribution (binomial)

  4. Various noncentral t distributions, including:

    • Noncentral t distribution (noncentral_t)

    • Noncentral t distribution scaled for a paired samples/one sample Cohen’s d (noncentral_d)

    • Noncentral t distribution scaled for an independent samples Cohen’s d (noncentral_d2)

Worked examples

For worked examples of the basic usage see basic usage. Or for basic plot functionality see basic plotting

Changelog

Breaking changes for < v0.9.0

distribution parameter for specifying likelihoods and priors has been renamed family

noncentral_d and noncentral_d2 are now parametrised in terms of sample size rather than df

About

The Bayesian playground. A package for learning Bayes factors

Resources

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md

Stars

Watchers

Forks

Packages

No packages published

Languages

  • R 100.0%