Dakota Reference Manual: dream

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dream

DREAM (DiffeRential Evolution Adaptive Metropolis)

## Topics

This keyword is related to the topics:

- bayesian_calibration

## 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 | chains | Number of chains in DREAM
| Optional | num_cr | Number of candidate points for each crossover.
| Optional | crossover_chain_pairs | Number of chains used in crossover.
| Optional | gr_threshold | Convergence tolerance for the Gelman-Rubin statistic
| Optional | jump_step | Number of generations a long jump step is taken
| Optional | emulator | Use an emulator or surrogate model to evaluate the likelihood function
| Optional | standardized_space | Perform Bayesian inference in standardized probability space
| Optional | export_chain_points_file | Export the MCMC chain to the specified filename

## Description

The DiffeRential Evolution Adaptive Metropolis algorithm is described in[89]. For the DREAM method, one can define the number of chains used with `chains` (minimum 3). The total number of generations per chain in DREAM is the number of samples (`samples`) divided by the number of chains (`chains`). The number of chains randomly selected to be used in the crossover each time a crossover occurs is `crossover_chain_pairs`. There is an extra adaptation during burn-in, in which DREAM estimates a distribution of crossover probabilities that favors large jumps over smaller ones in each of the chains. Normalization is required to ensure that all of the input dimensions contribute equally. In this process, a discrete number of candidate points for each crossover value is generated. This parameter is `num_cr`. The `gr_threshold` is the convergence tolerance for the Gelman-Rubin statistic which will govern the convergence of the multiple chain process. The integer `jump_step` forces a long jump every `jump_step` generations. For more details about these parameters, see[89].

Attention: While the `emulator` specification for DREAM includes the keyword posterior_adaptive, it is not yet operational.