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) .


CRAN_Status_Badge Build Status 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.

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install.packages("circglmbayes")

1.2.3 by Kees Mulder, a year ago


https://github.com/keesmulder/circglmbayes


Report a bug at https://github.com/keesmulder/circglmbayes/issues


Browse source code at https://github.com/cran/circglmbayes


Authors: Kees Mulder [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, stats, graphics, shiny, grDevices, ggplot2, reshape2, coda

Linking to Rcpp, BH, RcppArmadillo


See at CRAN