log_prior

Implements the Mode Jumping Markov Chain Monte Carlo algorithm described in <doi:10.1016/j.csda.2018.05.020> and its Genetically Modified counterpart described in <doi:10.1613/jair.1.13047> as well as the sub-sampling versions described in <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

log_prior function

<dl><dt>mlpost_params</dt>
<dd>list of passed parameters of the likelihood in GMJMCMC</dd>
<dt>complex</dt>
<dd>list of complexity measures of the features included into the model</dd></dl>

Arguments

Log model prior function — log_prior

<dl>

<dt>mlpost_params</dt>
<dd>list of passed parameters of the likelihood in GMJMCMC</dd>


<dt>complex</dt>
<dd>list of complexity measures of the features included into the model</dd>

</dl>

log_prior: Log model prior function

Description

Usage

Value

Arguments

Examples