This package contains functions to analyze circular regression type models (multivariate and mixed-effects). It is based on the 'embedding' approach to circular modelling and makes use of the projected normal distribution. Its estimation method is a Bayesian MCMC sampler. Further technical details can be found in Cremers, Mulder & Klugkist (2018) and Cremers & Klugkist (2018).
The main functions of the package are:
bpnr, which runs an MCMC sampler in C++ and returns an
S3 object of type bpnr, which can be further analyzed through
associated functions.
bpnme, which runs an MCMC sampler in R and returns an
S3 object of type bpnme, which can be further analyzed through
associated functions.
Datasets included in this package are:
Motor, A dataset from a study by Puglisi et.al. (2017) on the
role of attention in human motor resonance.
Maps, A dataset from a study by Warren et.al. (2017) on the
geometry of human knowledge of navigation space.
Maintainer: Jolien Cremers joliencremers@gmail.com
A tutorial on how to use this package can be found in Cremers & Klugkist (2018). More details on the sampling algorithm and interpretation of the coefficients from the model can be found in Cremers, Mulder & Klugkist (2018), Nuñez-Antonio & Gutiérrez-Peña, Cremers, Mainhard & Klugkist (2018) and Cremers, Pennings, Mainhard & Klugkist (2019).
Useful links: