Dakota Reference Manual  Version 6.12
Explore and Predict with Confidence
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Markov Chain Monte Carlo algorithms from the MUQ package


This keyword is related to the topics:


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

(Choose One)
MCMC Algorithm (Group 1) adaptive_metropolis

Use the Adaptive Metropolis MCMC algorithm


Use the Metropolis-Hastings MCMC algorithm


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.