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.