summary.gmjmcmc

Function to print a quick summary of the results

Implements MJMCMC (mode jumping MCMC) described in Hubin and Storvik (2018) <doi:10.1016/j.csda.2018.05.020> and GMJMCMC (genetically modified MJMCMC) described in Hubin et al. (2021) <doi:10.1613/jair.1.13047> algorithms as well as the subsampling counterpart described in Lachmann et al. (2022) <doi:10.1016/j.ijar.2022.08.018> for flexible Bayesian model selection and model averaging.

Jon Lachmann

FBMS

Flexible Bayesian Model Selection and Model Averaging

Aliaksandr Hubin

summary.gmjmcmc function

<dl><dt>object</dt>
<dd>The results to use</dd>
<dt>pop</dt>
<dd>The population to print for, defaults to last</dd>
<dt>tol</dt>
<dd>The tolerance to use as a threshold when reporting the results.</dd>
<dt>labels</dt>
<dd>Should the covariates be named, or just referred to as their place in the data.frame.</dd>
<dt>effects</dt>
<dd>Quantiles for posterior modes of the effects across models to be reported, if either effects are NULL or if labels are NULL, no effects are reported.</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Function to print a quick summary of the results — summary.gmjmcmc

<dl>

<dt>object</dt>
<dd>The results to use</dd>


<dt>pop</dt>
<dd>The population to print for, defaults to last</dd>


<dt>tol</dt>
<dd>The tolerance to use as a threshold when reporting the results.</dd>


<dt>labels</dt>
<dd>Should the covariates be named, or just referred to as their place in the data.frame.</dd>


<dt>effects</dt>
<dd>Quantiles for posterior modes of the effects across models to be reported, if either effects are NULL or if labels are NULL, no effects are reported.</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

summary.gmjmcmc: Function to print a quick summary of the results

Description

Usage

Value

Arguments

Examples