Dakota Reference Manual: uniform

| Dakota Reference Manual Version 6.15 Explore and Predict with Confidence

- Main Page
- Related Pages

All Pages
uniform

Refine an expansion uniformly in all dimensions.

## Specification

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

## Description

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.