beta_mean

Average the samples for the beta parameter from the VB posterior mean. This
is used to get predicted compositions when using <code>predict</code> on an lnm model.

Logistic-normal Multinomial (LNM) models are common in problems with multivariate count data. This package gives a simple implementation with a 30 line 'Stan' script. This lightweight implementation makes it an easy starting point for other projects, in particular for downstream tasks that require analysis of "compositional" data. It can be applied whenever a multinomial probability parameter is thought to depend linearly on inputs in a transformed, log ratio space. Additional utilities make it easy to inspect, create predictions, and draw samples using the fitted models. More about the LNM can be found in Xia et al. (2013) "A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis" <doi:10.1111/biom.12079> and Sankaran and Holmes (2023) "Generative Models: An Interdisciplinary Perspective" <doi:10.1146/annurev-statistics-033121-110134>.

Kris Sankaran

miniLNM

Miniature Logistic-Normal Multinomial Models

beta_mean function

<dl><dt>fit</dt>
<dd>An object of class <code>lnm</code> whose estimate slot contains the 'rstan'
fitted logistic normal multinomial model.</dd></dl>

Arguments

LNM Posterior Mean — beta_mean

<dl>

<dt>fit</dt>
<dd>An object of class <code>lnm</code> whose estimate slot contains the 'rstan'
fitted logistic normal multinomial model.</dd>

</dl>

beta_mean: LNM Posterior Mean

Description

Usage

Value

Arguments

Examples