Sandia National Laboratories

# mf_pce

Multifidelity Polynomial Chaos Expansion as an emulator model.

Specification

- Alias: None

- Arguments: None

Child Keywords:

Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | ---
Optional | p_refinement | Automatic polynomial order refinement
Optional | max_refinement_iterations | Maximum number of expansion refinement iterations
Optional | allocation_control | Sample allocation approach for multifidelity expansions
Optional | discrepancy_emulation | Formulation for emulation of model discrepancies.
Required (Choose One) | Required (Choose One) | quadrature_order_sequence | Sequence of quadrature orders used in a multi-stage expansion
sparse_grid_level_sequence | Sequence of sparse grid levels used in a multi-stage expansion
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 | 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 | diagonal_covariance | Display only the diagonal terms of the covariance matrix
full_covariance | Display the full covariance matrix

Description

Selects a multifidelity polynomial chaos expansion (MF PCE) surrogate model to use in the Bayesian likelihood calculations. Most specification options are carried over for using MF PCE as a surrogate within the Bayesian framework.

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