Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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wasabi


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

Specification

Alias: none

Argument(s): none

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

Seed of the random number generator

Optional emulator

Use an emulator or surrogate model to evaluate the likelihood function

Required data_distribution (Experimental Capability) Specify the distribution of the experimental data
Optional posterior_density_export_filename (Experimental Capability) Filename for the exported posterior density
Optional posterior_samples_export_filename (Experimental Capability) Filename for the exported posterior samples
Optional posterior_samples_import_filename (Experimental Capability) Filename for imported posterior samples
Optional generate_posterior_samples (Experimental Capability) Generate random samples from the posterior density

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