ppc_summary.pibblefit

ppc_summary

Generic Method to Plot Posterior Predictive Summaries

Provides methods for fitting and inspection of Bayesian Multinomial Logistic Normal Models using MAP estimation
and Laplace Approximation as developed in Silverman et. Al. (2022) <https://www.jmlr.org/papers/v23/19-882.html>. Key functionality is implemented in C++ for
scalability. 'fido' replaces the previous package 'stray'.

Michelle Nixon

fido

Bayesian Multinomial Logistic Normal Regression

Justin Silverman

Kim Roche

ppc_summary.pibblefit function

<dl><dt>m</dt>
<dd>model object</dd>
<dt>from_scratch</dt>
<dd>should predictions of Y come from fitted Eta or from 
predictions of Eta from posterior of Lambda? (default: false)</dd>
<dt>...</dt>
<dd>other arguments to pass</dd></dl>

Arguments

Generic Method to Plot Posterior Predictive Summaries — ppc_summary.pibblefit

<dl>

<dt>m</dt>
<dd>model object</dd>


<dt>from_scratch</dt>
<dd>should predictions of Y come from fitted Eta or from 
predictions of Eta from posterior of Lambda? (default: false)</dd>


<dt>...</dt>
<dd>other arguments to pass</dd>

</dl>

ppc_summary.pibblefit: Generic Method to Plot Posterior Predictive Summaries

Description

Usage

Value

Arguments