Dakota Reference Manual: standardized_space

| Dakota Reference Manual Version 6.15 Explore and Predict with Confidence

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standardized_space

Perform Bayesian inference in standardized probability space

## Specification

Alias: none

Argument(s): none

## Description

This option transforms the inference process (MCMC sampling and any emulator model management) into a standardized probability space.

The variable transformations performed are as described in askey.

Default Behavior

The default for the Gaussian process and no emulator options is to perform inference in the original probability space (no transformation). Polynomial chaos and stochastic collocation emulators, on the other hand, are always formed in standardized probability space, such that the inference process is also performed in this standardized space.

Expected Output

The user will see the truth model evaluations performed in the original space, whereas any method diagnostics relating to the MCMC samples (e.g., QUESO data in the outputData directory) will report points and response data (response gradients and Hessians, if present, will differ but response values will not) that correspond to the transformed space.

Usage Tips

Selecting standardized_space generally has the effect of scaling the random variables to be of comparable magnitude, which can improve the efficiency of the Bayesian inference process.

## Examples

    method,
            bayes_calibration queso
              samples = 2000 seed = 348
              dram
              standardized_space