combineChains

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

combineChains function

<dl><dt>x</dt>
<dd>a list of MCMC chains</dd>
<dt>merge</dt>
<dd>logical determines whether chains should be merged</dd></dl>

Arguments

Function to combine chains — combineChains

<dl>

<dt>x</dt>
<dd>a list of MCMC chains</dd>


<dt>merge</dt>
<dd>logical determines whether chains should be merged</dd>

</dl>

Function to combine chains

combineChains: Function to combine chains

Description

Usage

Value

Arguments