isBar

Function to help divide input formula of bpnme object into a fixed and random
part

internal

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>.

Jolien Cremers

bpnreg

Bayesian Projected Normal Regression Models for Circular Data

isBar function

<dl><dt>term</dt>
<dd>see lme4 package documentation</dd></dl>

Arguments

isBars function from lme4 package — isBar

<dl>

<dt>term</dt>
<dd>see lme4 package documentation</dd>

</dl>

isBar: isBars function from lme4 package

Description

Usage

Arguments