prior_summary.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

prior_summary.brmcoda function

<dl><dt>object</dt>
<dd>An object of class <code>brmcoda</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Extract Priors of a brmsfit from a brmcoda object — prior_summary.brmcoda

<dl>

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


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

prior_summary.brmcoda: Extract Priors of a `brmsfit` from a `brmcoda` object

Description

Usage

Arguments

See Also