mean.complr

Mean amounts and mean compositions presented in a <code>complr</code> object.

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

mean.complr function

<dl><dt>x</dt>
<dd>An object of class <code>complr</code>.</dd>
<dt>weight</dt>
<dd>A character value specifying the weight to use in calculation of the reference composition.
If <code>"equal"</code>, give equal weight to units (e.g., individuals).
If <code>"proportional"</code>, weights in proportion to the frequencies of units being averaged
(e.g., observations across individuals)
Default is <code>equal</code>.</dd>
<dt>...</dt>
<dd>generic argument, not in use.</dd></dl>

Arguments

Mean amounts and mean compositions presented in a complr object. — mean.complr

<dl>

<dt>x</dt>
<dd>An object of class <code>complr</code>.</dd>


<dt>weight</dt>
<dd>A character value specifying the weight to use in calculation of the reference composition.
If <code>"equal"</code>, give equal weight to units (e.g., individuals).
If <code>"proportional"</code>, weights in proportion to the frequencies of units being averaged
(e.g., observations across individuals)
Default is <code>equal</code>.</dd>


<dt>...</dt>
<dd>generic argument, not in use.</dd>

</dl>

mean.complr: Mean amounts and mean compositions presented in a `complr` object.

Description

Usage

Arguments

Examples