coef_circ.bpnr

Gives the coefficients tables of the circular coefficients for a Bayesian
circular regression model.

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

coef_circ.bpnr function

<dl><dt>object</dt>
<dd>a <code>bpnr object</code> obtained from the function
<code>bpnr</code></dd>
<dt>type</dt>
<dd>one of <code>c("continuous", "categorical")</code> to get either the
coefficients for the continuous or categorical predictor variables</dd>
<dt>units</dt>
<dd>one of <code>c("degrees", "radians")</code> to get categorical
coefficients estimates and estimates for <code>$ac$, $bc$, AS and SAM</code> in degrees or
radians.</dd></dl>

Arguments

Obtain the circular coefficients of a Bayesian circular regression model — coef_circ.bpnr

<dl>

<dt>object</dt>
<dd>a <code>bpnr object</code> obtained from the function
<code>bpnr</code></dd>


<dt>type</dt>
<dd>one of <code>c("continuous", "categorical")</code> to get either the
coefficients for the continuous or categorical predictor variables</dd>


<dt>units</dt>
<dd>one of <code>c("degrees", "radians")</code> to get categorical
coefficients estimates and estimates for <code>$ac$, $bc$, AS and SAM</code> in degrees or
radians.</dd>

</dl>

coef_circ.bpnr: Obtain the circular coefficients of a Bayesian circular regression model

Description

Usage

Value

Arguments

Examples