makeObjectClassCodaMCMC

Helper function to change an object to a coda mcmc class,

internal

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

makeObjectClassCodaMCMC function

<dl><dt>chain</dt>
<dd>mcmc Chain</dd>
<dt>start</dt>
<dd>for mcmc samplers start value in the chain. For SMC samplers, start particle</dd>
<dt>end</dt>
<dd>for mcmc samplers end value in the chain. For SMC samplers, end particle</dd>
<dt>thin</dt>
<dd>thinning parameter</dd></dl>

Arguments

Helper function to change an object to a coda mcmc class, — makeObjectClassCodaMCMC

<dl>

<dt>chain</dt>
<dd>mcmc Chain</dd>


<dt>start</dt>
<dd>for mcmc samplers start value in the chain. For SMC samplers, start particle</dd>


<dt>end</dt>
<dd>for mcmc samplers end value in the chain. For SMC samplers, end particle</dd>


<dt>thin</dt>
<dd>thinning parameter</dd>

</dl>

makeObjectClassCodaMCMC: Helper function to change an object to a coda mcmc class,

Description

Usage

Value

Arguments

Details