wasabi

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

Specification

• Alias: None

• Arguments: 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
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
Optional		evaluate_posterior_density	(Experimental Capability) Evaluate the posterior density and output to the specified file

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