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)
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
For further help on this package, install it as above, attach it with
library(circglmbayes) and run