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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Multilevel Polynomial Chaos Expansion as an emulator model.
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | allocation_control | Sample allocation approach for multilevel expansions | ||
Optional | discrepancy_emulation | Formulation for emulation of model discrepancies. | ||
Required (Choose One) | Group 1 | expansion_order_sequence | Sequence of expansion orders used in a multi-stage expansion | |
orthogonal_least_interpolation | Build a polynomial chaos expansion from simulation samples using orthogonal least interpolation. | |||
Optional (Choose One) | Basis Polynomial Family (Group 2) | askey | Select the standardized random variables (and associated basis polynomials) from the Askey family that best match the user-specified random variables. | |
wiener | Use standard normal random variables (along with Hermite orthogonal basis polynomials) when transforming to a standardized probability space. | |||
Optional | normalized | The normalized specification requests output of PCE coefficients that correspond to normalized orthogonal basis polynomials | ||
Optional | export_expansion_file | Export the coefficients and multi-index of a Polynomial Chaos Expansion (PCE) to a file | ||
Optional (Choose One) | Covariance Type (Group 3) | diagonal_covariance | Display only the diagonal terms of the covariance matrix | |
full_covariance | Display the full covariance matrix |
Selects a multilevel polynomial chaos expansion (ML PCE) surrogate model to use in the Bayesian likelihood calculations. Most specification options are carried over for using ML PCE as a surrogate within the Bayesian framework.
These keywords may also be of interest: