Dakota Reference Manual: wasabi

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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