Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
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wasabi


(Experimental Method) Non-MCMC Bayesian inference using interval analysis

Specification

Alias: none

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Required pushforward_samples

(Experimental Capability) Number of samples of the prior to push forward through the model

Description: WASABI requires a forward UQ that maps samples from the prior parameter distribution through the model. The corresponding responses then are used to see their relative likelihood according to the density of the observational data. The pushforward_samples refers to the number of samples taken from the prior and used in the forward UQ. It typically should be high, e.g. 10000, of which only a small fraction may be in a high density region of the posterior.

Optional seed

Seed of the random number generator

Optional emulator

Use an emulator or surrogate model to evaluate the likelihood function

Optional standardized_space

Perform Bayesian inference in standardized probability space

Required data_distribution (Experimental Capability) Specify the distribution of the experimental data
Optional posterior_samples_import_filename (Experimental Capability) Filename for samples at which the user would like the posterior density calculated
Optional generate_posterior_samples

(Experimental Capability) Generate random samples from the posterior density

Description: This keyword will result in samples from the prior that have a high posterior density being printed to a file called 'psamples.txt' as a default, or to a file specified by the posterior_samples_export_filename.

Optional evaluate_posterior_density

(Experimental Capability) Evaluate the posterior density and output to the specified file

Description: This keyword will allow the evaluation of the posterior density for all of the prior samples, typically specified with the number given in pushforward_samples. The density will be printed either to a file named 'pdens.txt' as a default, or to the file specified in posterior_density_export_filename.

Description

Offers an alternative to Markov Chain Monte Carlo-based Bayesian inference. This is a nascent capability, not yet ready for production use.

Usage Guidelines: The WASABI method requires an emulator model.

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

Examples

method
  bayes_calibration
    wasabi