Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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least_squares


Compute the coefficients of a polynomial expansion using least squares

Specification

Alias: none

Argument(s): none

Default: svd

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional
(Choose One)
Group 1 svd Calculate the coefficients of a polynomial chaos expansion using the singular value decomposition.
equality_constrained Calculate the coefficients of a polynomial chaos expansion using equality constrained least squares.

Description

Compute the coefficients of a polynomial expansion using least squares. Specifically SVD-based least-squares will be used for solving over-determined systems. For the situation when the number of function values is smaller than the number of terms in a PCE, but the total number of samples including gradient values is greater than the number of terms, the resulting over-determined system will be solved using equality constrained least squares