checkBayesianSetup

Function used to assure that an object is of class 'BayesianSetup'. If you pass a function, it is coverted to an object of class 'BayesianSetup' (using <code>createBayesianSetup</code>) before it is returned.

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

checkBayesianSetup function

<dl><dt>bayesianSetup</dt>
<dd>either object of class bayesianSetup or a log posterior function</dd>
<dt>parallel</dt>
<dd>if bayesianSetup is a function, this will set the parallelization option for the class BayesianSetup that is created internally. If bayesianSetup is already a BayesianSetup, then this will check if parallel = T is requested but not supported by the BayesianSetup. This option is for internal use in the samplers</dd></dl>

Arguments

Author

Checks if an object is of class 'BayesianSetup' — checkBayesianSetup

<dl>

<dt>bayesianSetup</dt>
<dd>either object of class bayesianSetup or a log posterior function</dd>


<dt>parallel</dt>
<dd>if bayesianSetup is a function, this will set the parallelization option for the class BayesianSetup that is created internally. If bayesianSetup is already a BayesianSetup, then this will check if parallel = T is requested but not supported by the BayesianSetup. This option is for internal use in the samplers</dd>

</dl>

checkBayesianSetup: Checks if an object is of class 'BayesianSetup'

Description

Usage

Arguments

Author

See Also