bayes_factor.brmcoda

Compute Bayes factors from marginal likelihoods

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

bayes_factor.brmcoda function

<dl><dt>x1</dt>
<dd>A <code>brmcoda</code> object.</dd>
<dt>x2</dt>
<dd>Another <code>brmcoda</code> object based on the same responses.</dd>
<dt>...</dt>
<dd>Other arguments passed to <code>bayes_factor.brmsfit</code>.</dd></dl>

Arguments

Bayes Factors from Marginal Likelihoods — bayes_factor.brmcoda

<dl>

<dt>x1</dt>
<dd>A <code>brmcoda</code> object.</dd>


<dt>x2</dt>
<dd>Another <code>brmcoda</code> object based on the same responses.</dd>


<dt>...</dt>
<dd>Other arguments passed to <code>bayes_factor.brmsfit</code>.</dd>

</dl>

bayes_factor.brmcoda: Bayes Factors from Marginal Likelihoods

Description

Usage

Arguments

See Also