gamma_data_1

Simulated data to show how the gamma 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

gamma_data_1 function

A data frame containing 1500 observations and 5 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>y</dt><dd>The response.</dd>
</dl>

Format

Simulated data to show how the gamma model may be fit with fixed and random effects on both the mean and dispersion. — gamma_data_1

A data frame containing 1500 observations and 5 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>y</dt><dd>The response.</dd>
</dl>

gamma_data_1: Simulated data to show how the gamma model may be fit with fixed and random effects on both the mean and dispersion.

Description

Usage

Arguments

Format