ml_pce

Multilevel 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

allocation_control

Sample allocation approach for multilevel expansions

Optional

discrepancy_emulation

Formulation for emulation of model discrepancies.

Required (Choose One)

Required (Choose One)

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 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.