pnme

A Gibbs sampler for a projected normal mixed-effects 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

pnme function

<dl><dt>theta_cos</dt>
<dd>A List with the cosine of the circular dependent variable.</dd>
<dt>theta_sin</dt>
<dd>A List with the sine of the circular dependent variable.</dd>
<dt>X1</dt>
<dd>A list of fixed effect model matrices for component I.</dd>
<dt>X2</dt>
<dd>A list of fixed effect model matrices for component II.</dd>
<dt>Z1</dt>
<dd>A list of random effect model matrices for component I.</dd>
<dt>Z2</dt>
<dd>A list of random effect model matrices for component II.</dd>
<dt>ZtZ1</dt>
<dd>A list of transformed random effect model matrices for component I.</dd>
<dt>ZtZ2</dt>
<dd>A list of transformed random effect model matrices for component II.</dd>
<dt>R</dt>
<dd>A list of starting values for R.</dd>
<dt>pred</dt>
<dd>An empty list for likelihood computation.</dd>
<dt>its</dt>
<dd>An integer specifying the number of iterations</dd>
<dt>lag</dt>
<dd>An integer specifying the amount of lag.</dd>
<dt>burn</dt>
<dd>An integer specifying the number of burn-in iterations.</dd>
<dt>N</dt>
<dd>An integer specifying the number of burn-in iterations.</dd></dl>

Arguments

A Gibbs sampler for a projected normal mixed-effects model — pnme

<dl>

<dt>theta_cos</dt>
<dd>A List with the cosine of the circular dependent variable.</dd>


<dt>theta_sin</dt>
<dd>A List with the sine of the circular dependent variable.</dd>


<dt>X1</dt>
<dd>A list of fixed effect model matrices for component I.</dd>


<dt>X2</dt>
<dd>A list of fixed effect model matrices for component II.</dd>


<dt>Z1</dt>
<dd>A list of random effect model matrices for component I.</dd>


<dt>Z2</dt>
<dd>A list of random effect model matrices for component II.</dd>


<dt>ZtZ1</dt>
<dd>A list of transformed random effect model matrices for component I.</dd>


<dt>ZtZ2</dt>
<dd>A list of transformed random effect model matrices for component II.</dd>


<dt>R</dt>
<dd>A list of starting values for R.</dd>


<dt>pred</dt>
<dd>An empty list for likelihood computation.</dd>


<dt>its</dt>
<dd>An integer specifying the number of iterations</dd>


<dt>lag</dt>
<dd>An integer specifying the amount of lag.</dd>


<dt>burn</dt>
<dd>An integer specifying the number of burn-in iterations.</dd>


<dt>N</dt>
<dd>An integer specifying the number of burn-in iterations.</dd>

</dl>

Get 50% off unlimited learning

pnme: A Gibbs sampler for a projected normal mixed-effects model

Description

Usage

Arguments