circ_coef

<code>circ_coef</code> computes the coordinates of the inflection point of
a circular effect, the slope at the inflection point and the unsigned and
signed shortest distance to the origin.

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

circ_coef function

<dl><dt>a1</dt>
<dd>intercept of the first linear component.</dd>
<dt>a2</dt>
<dd>intercept of the second linear component.</dd>
<dt>b1</dt>
<dd>slope of the first linear component.</dd>
<dt>b2</dt>
<dd>slope of the second linear component.</dd></dl>

Arguments

Compute circular coefficients from linear coefficients — circ_coef

<dl>

<dt>a1</dt>
<dd>intercept of the first linear component.</dd>


<dt>a2</dt>
<dd>intercept of the second linear component.</dd>


<dt>b1</dt>
<dd>slope of the first linear component.</dd>


<dt>b2</dt>
<dd>slope of the second linear component.</dd>

</dl>

circ_coef: Compute circular coefficients from linear coefficients

Description

Usage

Value

Arguments