Gfun

Helper function for blow and hop moves

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

Gfun function

<dl><dt>case</dt>
<dd>Type of Twalk move. Either "hop" or "blow"</dd>
<dt>npSel</dt>
<dd>number of parameters that are changed.</dd>
<dt>pSel</dt>
<dd>vector containing information about which parameters are changed.</dd>
<dt>h</dt>
<dd>Parameter for "blow" and hop moves</dd>
<dt>x</dt>
<dd>parameter vector of chain 1</dd>
<dt>x2</dt>
<dd>parameter vector of chain 2</dd></dl>

Arguments

Helper function for blow and hop moves — Gfun

<dl>

<dt>case</dt>
<dd>Type of Twalk move. Either "hop" or "blow"</dd>


<dt>npSel</dt>
<dd>number of parameters that are changed.</dd>


<dt>pSel</dt>
<dd>vector containing information about which parameters are changed.</dd>


<dt>h</dt>
<dd>Parameter for "blow" and hop moves</dd>


<dt>x</dt>
<dd>parameter vector of chain 1</dd>


<dt>x2</dt>
<dd>parameter vector of chain 2</dd>

</dl>

Gfun: Helper function for blow and hop moves

Description

Usage

Arguments

References