marginal.probs

Function for calculating marginal inclusion probabilities of features given a list of models

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

marginal.probs function

<dl><dt>models</dt>
<dd>The list of models to use.</dd></dl>

Arguments

Function for calculating marginal inclusion probabilities of features given a list of models — marginal.probs

<dl>

<dt>models</dt>
<dd>The list of models to use.</dd>

</dl>

marginal.probs: Function for calculating marginal inclusion probabilities of features given a list of models

Description

Usage

Value

Arguments

Examples