circglmbayes: 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) <doi:10.1016/>.

Version: 1.2.3
Depends: R (≥ 2.10)
Imports: Rcpp, stats, graphics, shiny, grDevices, ggplot2, reshape2, coda
LinkingTo: Rcpp, BH, RcppArmadillo
Published: 2018-03-09
Author: Kees Mulder [aut, cre]
Maintainer: Kees Mulder <keestimmulder at>
License: GPL-3
NeedsCompilation: yes
Citation: circglmbayes citation info
Materials: README
CRAN checks: circglmbayes results


Reference manual: circglmbayes.pdf
Package source: circglmbayes_1.2.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: circglmbayes_1.2.3.tgz
OS X Mavericks binaries: r-oldrel: not available


Please use the canonical form to link to this page.