updateGroups

Determine the groups of correlated parameters

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

updateGroups function

<dl><dt>chain</dt>
<dd>MCMC chain including only the parameters (not logP,ll, logP)</dd>
<dt>blockSettings</dt>
<dd>list with settings</dd></dl>

Arguments

Author

Determine the groups of correlated parameters — updateGroups

<dl>

<dt>chain</dt>
<dd>MCMC chain including only the parameters (not logP,ll, logP)</dd>


<dt>blockSettings</dt>
<dd>list with settings</dd>

</dl>

updateGroups: Determine the groups of correlated parameters

Description

Usage

Value

Arguments

Author