Bayesian Analysis of a Circular GLM

Perform a Bayesian analysis of a circular outcome General Linear Model (GLM), which allows regressing a circular outcome on linear and categorical predictors. Posterior samples are obtained by means of an MCMC algorithm written in 'C++' through 'Rcpp'. Estimation and credible intervals are provided, as well as hypothesis testing through Bayes Factors. See Mulder and Klugkist (2017) .

R Package for a Bayesian Circular GLM

This package contains functions to perform a Bayesian circular GLM, which allows regressing a circular outcome on linear and categorical predictors.

In order to use this package from R, it can be installed from GitHub using the devtools package as

install.packages("devtools")
devtools::install_github("keesmulder/circglmbayes")

For further help on this package, install it as above, attach it with library(circglmbayes) and run help("circglmbayes") or ?circGLM.