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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Generic UQ method for constructing and interrogating a surrogate model.
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | samples_on_emulator | Number of samples at which to evaluate an emulator (surrogate) | ||
Optional | sample_type | Selection of sampling strategy | ||
Optional | rng | Selection of a random number generator | ||
Optional | probability_refinement | Allow refinement of probability and generalized reliability results using importance sampling | ||
Optional | final_moments | Output moments of the specified type and include them within the set of final statistics. | ||
Optional | response_levels | Values at which to estimate desired statistics for each response | ||
Optional | probability_levels | Specify probability levels at which to estimate the corresponding response value | ||
Optional | reliability_levels | Specify reliability levels at which the response values will be estimated | ||
Optional | gen_reliability_levels | Specify generalized relability levels at which to estimate the corresponding response value | ||
Optional | distribution | Selection of cumulative or complementary cumulative functions | ||
Optional | variance_based_decomp | Activates global sensitivity analysis based on decomposition of response variance into main, interaction, and total effects | ||
Optional (Choose One) | Covariance Type (Group 1) | diagonal_covariance | Display only the diagonal terms of the covariance matrix | |
full_covariance | Display the full covariance matrix | |||
Optional | import_approx_points_file | Filename for points at which to evaluate the PCE/SC surrogate | ||
Optional | export_approx_points_file | Output file for surrogate model value evaluations | ||
Optional | seed | Seed of the random number generator | ||
Optional | fixed_seed | Reuses the same seed value for multiple random sampling sets | ||
Optional | model_pointer | Identifier for model block to be used by a method |
As surrogate models by stochastic expansion migrate into the model specification, this method provides a general-purpose UQ method to interrogate the surrogate for generating statistics.
This method must identify the surrogate of interest through its model_pointer
, distinguishing it from fully-integrated method specifications such as polynomial_chaos, stoch_collocation, and function_train that couple directly with a simulation model (and form the PCE, SC, FT surrogate approximations implicitly prior to using them for generating statistics).
These keywords may also be of interest: