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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Refine an expansion uniformly in all dimensions.
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Required (Choose One) | Uniform Refinement Approach (Group 1) | increment_start_rank | candidate generation by advancement of starting rank | |
increment_start_order | candidate generation by advancement of starting basis order | |||
increment_max_rank | candidate generation by advancement of maximum rank | |||
increment_max_order | candidate generation by advancement of maximum basis order | |||
increment_max_rank_order | candidate generation by advancement of maximum rank and maximum basis order |
The quadrature_order or sparse_grid_level are ramped by one on each refinement iteration until either of the two convergence controls is satisfied. For the uniform refinement case with regression approaches, the expansion_order is ramped by one on each iteration while the oversampling ratio (either defined by collocation_ratio or inferred from collocation_points based on the initial expansion) is held fixed.