diagn_plot

Plot convergence of best/median/mean/other summary log posteriors in time

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

diagn_plot function

<dl><dt>res</dt>
<dd>Object corresponding gmjmcmc output</dd>
<dt>FUN</dt>
<dd>The summary statistics to check convergence</dd>
<dt>conf</dt>
<dd>which confidence intervals to plot</dd>
<dt>burnin</dt>
<dd>how many first populations to skip</dd>
<dt>window</dt>
<dd>sliding window for computing the standard deviation</dd>
<dt>ylim</dt>
<dd>limits for the plotting range, if unspecified, min and max of confidence intervals will be used</dd></dl>

Arguments

Plot convergence of best/median/mean/other summary log posteriors in time — diagn_plot

<dl>

<dt>res</dt>
<dd>Object corresponding gmjmcmc output</dd>


<dt>FUN</dt>
<dd>The summary statistics to check convergence</dd>


<dt>conf</dt>
<dd>which confidence intervals to plot</dd>


<dt>burnin</dt>
<dd>how many first populations to skip</dd>


<dt>window</dt>
<dd>sliding window for computing the standard deviation</dd>


<dt>ylim</dt>
<dd>limits for the plotting range, if unspecified, min and max of confidence intervals will be used</dd>

</dl>

diagn_plot: Plot convergence of best/median/mean/other summary log posteriors in time

Description

Usage

Value

Arguments

Examples