muq

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• Keywords Area
• method
• bayes_calibration
• muq

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Markov Chain Monte Carlo algorithms from the MUQ package

Topics

This keyword is related to the topics:

• bayesian_calibration
• topic-package_muq

Specification

Alias: none

Argument(s): none

Child Keywords:

	Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
	Required		chain_samples	Number of Markov Chain Monte Carlo posterior samples
	Optional		seed	Seed of the random number generator
	Optional		rng	Selection of a random number generator
	Optional (Choose One)	MCMC Algorithm (Group 1)	adaptive_metropolis	Use the Adaptive Metropolis MCMC algorithm
			metropolis_hastings	Use the Metropolis-Hastings MCMC algorithm

Description

The muq method supports the following MCMC algorithms: adaptive metropolis (AM) or pure Metropolis Hasting (MH).

The muq method is currently an experimental method that relies on algorithms from MIT's MUQ code documented at: https://bitbucket.org/mituq/muq2/src/master/

We anticipate using more advanced features of MUQ such as Hamiltonian Monte Carlo and Langevin methods in future releases of Dakota.

This