efficient_subspace

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• Keywords Area
• method
• efficient_subspace

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(Experimental) efficient subspace method (ESM)

Topics

This keyword is related to the topics:

• uncertainty_quantification

Specification

Alias: nond_efficient_subspace

Argument(s): none

	Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
	Optional		emulator_samples	Number of data points used to train the surrogate model or emulator
	Optional		batch_size	The number of points to add in each batch.
	Optional		distribution	Selection of cumulative or complementary cumulative functions
	Optional		probability_levels	Specify probability levels at which to estimate the corresponding response value
	Optional		gen_reliability_levels	Specify generalized relability levels at which to estimate the corresponding response value
	Optional		rng	Selection of a random number generator
	Optional		samples	Number of samples for sampling-based methods
	Optional		seed	Seed of the random number generator
	Optional		model_pointer	Identifier for model block to be used by a method

Description

ESM is experimental and its implementation is incomplete. It is an active subspace method, intended for use with models with high dimensional input parameter spaces and analytic gradients. The method works by evaluating the response gradient at a number of points in the input parameter space and using a singular value decomposition to identify key linear combinations of input directions along which the response varies. Then UQ is performed in the reduced input parameter space.