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.
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")
The bayesplay
package comes with three basic functions for computing
Bayes factors.
-
The
likelihood()
function for specifying likelihoods -
The
prior()
function for specifying priors -
And the
integral()
function
Currently the following distributions are supported for likelihoods and priors
-
Normal distribution (
normal
) -
Uniform distribution (
uniform
) -
Scaled and shifted t distribution (
student_t
) -
Cauchy distributions (
cauchy
) -
Beta distribution (
beta
)
-
Normal distribution (
normal
) -
Scaled and shifted t distribution (
student_t
) -
Binomial distribution (
binomial
) -
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
)
-
For worked examples of the basic usage see basic usage. Or for basic plot functionality see basic plotting
Breaking changes for < v0.9.0
distribution
parameter for specifying likelihoods and priors has been renamedfamily
noncentral_d
andnoncentral_d2
are now parametrised in terms of sample size rather than df