Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
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collocation_points


Number of collocation points used to estimate expansion coefficients

Specification

Alias: none

Argument(s): INTEGER

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional
(Choose One)
Regression Algorithm (Group 1) least_squares Compute the coefficients of a polynomial expansion using least squares
orthogonal_matching_pursuit Compute the coefficients of a polynomial expansion using orthogonal matching pursuit (OMP)
basis_pursuit Compute the coefficients of a polynomial expansion by solving the Basis Pursuit $\ell_1$-minimization problem using linear programming.
basis_pursuit_denoising Compute the coefficients of a polynomial expansion by solving the Basis Pursuit Denoising $\ell_1$-minimization problem using second order cone optimization.
least_angle_regression Compute the coefficients of a polynomial expansion by using the greedy least angle regression (LAR) method.
least_absolute_shrinkage Compute the coefficients of a polynomial expansion by using the LASSO problem.
Optional cross_validation Use cross validation to choose the 'best' polynomial order of a polynomial chaos expansion.
Optional ratio_order Specify a non-linear the relationship between the expansion order of a polynomial chaos expansion and the number of samples that will be used to compute the PCE coefficients.
Optional response_scaling

Perform bounds-scaling on response values prior to surrogate emulation

Optional use_derivatives

Use derivative data to construct surrogate models

Optional tensor_grid Use sub-sampled tensor-product quadrature points to build a polynomial chaos expansion.
Optional reuse_points This describes the behavior of reuse of points in constructing polynomial chaos expansion models.
Optional max_solver_iterations

Maximum iterations in determining polynomial coefficients

Description

Specify the number of collocation points used to estimate expansion coefficients using regression approaches.

A corresponding sequence specification is documented at, e.g., collocation_points_sequence and collocation_points_sequence

See Also

These keywords may also be of interest:

  • collocation_points_sequence method-multilevel_polynomial_chaos-expansion_order_sequence-collocation_ratio-collocation_points_sequence