betabin_data_1

Simulated data to show how the beta-binomial model may be fit with fixed and random effects on both the mean and dispersion.

datasets

Automates fitting of double GLM in 'JAGS'. Includes automatic
generation of 'JAGS' scripts, running 'JAGS' or 'nimble' via the 'rjags'
and 'nimble' package, and summarizing the resulting output. For further
information see Bonner, Kim, Westneat, Mutzel, Wright, and Schofield
<doi:10.18637/jss.v100.i10>.

Simon Bonner

dalmatian

Automating the Fitting of Double Linear Mixed Models in 'JAGS'
and 'nimble'

Hanna Kim

betabin_data_1 function

A data frame containing 500 observations and 6 columns:<dl class="dl-horizontal">
 <dt>ID</dt><dd>The individual ID.</dd>
 <dt>Rep</dt><dd>The replicate number</dd>.
 <dt>x1</dt><dd>The value of the covariate for the mean.</dd>
 <dt>x2</dt><dd>The value of the covariate for the dispersion.</dd>
 <dt>m</dt><dd>The number of Bernoulli trials for each observation.</dd>
 <dt>y</dt><dd>The number of successes.</dd>
</dl>

Format

Simulated data for illustrating the beta-binomial model — betabin_data_1

A data frame containing 500 observations and 6 columns:<dl class='dl-horizontal'>
 <dt>ID</dt><dd>The individual ID.</dd>
 <dt>Rep</dt><dd>The replicate number</dd>.
 <dt>x1</dt><dd>The value of the covariate for the mean.</dd>
 <dt>x2</dt><dd>The value of the covariate for the dispersion.</dd>
 <dt>m</dt><dd>The number of Bernoulli trials for each observation.</dd>
 <dt>y</dt><dd>The number of successes.</dd>
</dl>

betabin_data_1: Simulated data for illustrating the beta-binomial model

Description

Usage

Arguments

Format