keesmulder/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/j.jmp.2017.07.001>.

Getting started

Package details

MaintainerKees Mulder <keestimmulder@gmail.com>
LicenseGPL-3
Version1.3.0
URL https://github.com/keesmulder/circglmbayes
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("keesmulder/CircGLMBayes")
keesmulder/CircGLMBayes documentation built on Jan. 23, 2021, 2:49 a.m.