pp_check.brmcoda

pp_check

Perform posterior predictive checks with the help of the bayesplot package.

Implement Bayesian Multilevel Modelling for compositional data
in a multilevel framework. Compute multilevel compositional data and
Isometric log ratio (ILR) at between and within-person levels,
fit Bayesian multilevel models for compositional predictors and outcomes,
and run post-hoc analyses such as isotemporal substitution models.
References:
Le, Stanford, Dumuid, and Wiley (2024) <doi:10.48550/arXiv.2405.03985>,
Le, Dumuid, Stanford, and Wiley (2024) <doi:10.48550/arXiv.2411.12407>.

Flora Le

multilevelcoda

Estimate Bayesian Multilevel Models for Compositional Data

Joshua F. Wiley

pp_check.brmcoda function

<dl><dt>object</dt>
<dd>An object of class <code>brmcoda</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>predict.brmsfit</code>
as well as to the PPC function specified in <code>type</code>.</dd></dl>

Arguments

Posterior Predictive Checks for brmcoda Objects — pp_check.brmcoda

<dl>

<dt>object</dt>
<dd>An object of class <code>brmcoda</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to <code>predict.brmsfit</code>
as well as to the PPC function specified in <code>type</code>.</dd>

</dl>

pp_check.brmcoda: Posterior Predictive Checks for `brmcoda` Objects

Description

Usage

Arguments

See Also