predict.mjmcmc_parallel

Predict using a mjmcmc result object from a parallel run.

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

predict.mjmcmc_parallel function

<dl><dt>object</dt>
<dd>The model to use.</dd>
<dt>x</dt>
<dd>The new data to use for the prediction, a matrix where each row is an observation.</dd>
<dt>link</dt>
<dd>The link function to use</dd>
<dt>quantiles</dt>
<dd>The quantiles to calculate credible intervals for the posterior moddes (in model space).</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Predict using a mjmcmc result object from a parallel run. — predict.mjmcmc_parallel

<dl>

<dt>object</dt>
<dd>The model to use.</dd>


<dt>x</dt>
<dd>The new data to use for the prediction, a matrix where each row is an observation.</dd>


<dt>link</dt>
<dd>The link function to use</dd>


<dt>quantiles</dt>
<dd>The quantiles to calculate credible intervals for the posterior moddes (in model space).</dd>


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

</dl>

predict.mjmcmc_parallel: Predict using a mjmcmc result object from a parallel run.

Description

Usage

Value

Arguments

Examples