.averagePosterior

Internal function that averages over posterior predictions
using either <code><a href="/link/rowMeans()?package=brmsmargins&version=0.2.1" data-mini-rdoc="brmsmargins::rowMeans()">rowMeans()</a></code> or <code>rowBootMeans()</code>, the latter
being useful to incorporate uncertainty from the
inputs being used to generate predictions.

internal

Calculate Bayesian marginal effects, average marginal effects, and marginal coefficients (also called population averaged coefficients) for models fit using the 'brms' package including fixed effects, mixed effects, and location scale models. These are based on marginal predictions that integrate out random effects if necessary (see for example <doi:10.1186/s12874-015-0046-6> and <doi:10.1111/biom.12707>).

Joshua F Wiley

brmsmargins

Bayesian Marginal Effects for 'brms' Models

Joshua F. Wiley

Donald Hedeker

.averagePosterior function

<dl><dt>posterior</dt>
<dd>A posterior matrix type object. It is assumed that different
predictions to be averaged over are on different columns. Different posterior
draws are on different rows.</dd>
<dt>resample</dt>
<dd>An integer indicating the number of
bootstrap resamples of the posterior predictions to
use when calculating summaries. Defaults to <code>0L</code>.
See the details section for more information as its implementation
is experimental and it may not operate as one would expect.</dd>
<dt>seed</dt>
<dd>A seed for random number generation. Defaults to <code>FALSE</code>,
which means no seed is set.
Only used if <code>resample</code> is a positive, non-zero integer.</dd></dl>

Arguments

Internal function that averages over posterior predictions
using either <code><a href='https://rdrr.io/r/base/colSums.html'>rowMeans()</a></code> or <code>rowBootMeans()</code>, the latter
being useful to incorporate uncertainty from the
inputs being used to generate predictions.

Average Over Posterior Predictions — .averagePosterior

<dl>

<dt>posterior</dt>
<dd>A posterior matrix type object. It is assumed that different
predictions to be averaged over are on different columns. Different posterior
draws are on different rows.</dd>


<dt>resample</dt>
<dd>An integer indicating the number of
bootstrap resamples of the posterior predictions to
use when calculating summaries. Defaults to <code>0L</code>.
See the details section for more information as its implementation
is experimental and it may not operate as one would expect.</dd>


<dt>seed</dt>
<dd>A seed for random number generation. Defaults to <code>FALSE</code>,
which means no seed is set.
Only used if <code>resample</code> is a positive, non-zero integer.</dd>

</dl>

.averagePosterior: Average Over Posterior Predictions

Description

Usage

Value

Arguments