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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>.
Package details 


Author  Kees Mulder [aut, cre] 
Maintainer  Kees Mulder <keestimmulder@gmail.com> 
License  GPL3 
Version  1.2.3 
URL  https://github.com/keesmulder/circglmbayes 
Package repository  View on CRAN 
Installation 
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