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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Compute the coefficients of a polynomial expansion using least squares
Alias: none
Argument(s): none
Default: svd
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional (Choose One) | LSQ Regression Approach (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. |
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