bpnreg: Bayesian Projected Normal Regression Models for Circular Data

Fitting Bayesian multiple and mixed-effect regression models for circular data based on the projected normal distribution. Both continuous and categorical predictors can be included. Sampling from the posterior is performed via an MCMC algorithm. Posterior descriptives of all parameters, model fit statistics and Bayes factors for hypothesis tests for inequality constrained hypotheses are provided. See Cremers, Mulder & Klugkist (2018) <doi:10.1111/bmsp.12108> and Nuñez-Antonio & Guttiérez-Peña (2014) <doi:10.1016/j.csda.2012.07.025>.

Getting started

Package details

AuthorJolien Cremers [aut, cre]
MaintainerJolien Cremers <[email protected]>
LicenseGPL-3
Version1.0.0
URL https://github.com/joliencremers/bpnreg
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bpnreg")

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bpnreg documentation built on March 18, 2018, 2:01 p.m.