createPosterior

Creates a standardized posterior class

General-purpose MCMC and SMC samplers, as well as plot and
diagnostic functions for Bayesian statistics, with a particular focus on
calibrating complex system models. Implemented samplers include various
Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the
T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential
Monte Carlo (SMC) particle filter.

Florian Hartig

BayesianTools

General-Purpose MCMC and SMC Samplers and Tools for Bayesian
Statistics

Francesco Minunno

Stefan  Paul

David Cameron

Tankred Ott

Maximilian Pichler

createPosterior function

<dl><dt>prior</dt>
<dd>prior class</dd>
<dt>likelihood</dt>
<dd>Log likelihood density</dd></dl>

Arguments

Author

Creates a standardized posterior class — createPosterior

<dl>

<dt>prior</dt>
<dd>prior class</dd>


<dt>likelihood</dt>
<dd>Log likelihood density</dd>

</dl>

createPosterior: Creates a standardized posterior class

Description

Usage

Arguments

Author

Details