.. _method-multifidelity_function_train-p_refinement-uniform:

"""""""
uniform
"""""""


Refine an expansion uniformly in all dimensions.


.. toctree::
   :hidden:
   :maxdepth: 1

   method-multifidelity_function_train-p_refinement-uniform-increment_start_rank
   method-multifidelity_function_train-p_refinement-uniform-increment_start_order
   method-multifidelity_function_train-p_refinement-uniform-increment_max_rank
   method-multifidelity_function_train-p_refinement-uniform-increment_max_order
   method-multifidelity_function_train-p_refinement-uniform-increment_max_rank_order


**Specification**

- *Alias:* None

- *Arguments:* None


**Child Keywords:**

+-------------------------+--------------------+------------------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword               | Dakota Keyword Description                    |
|                         | Group              |                              |                                               |
+=========================+====================+==============================+===============================================+
| Required (Choose One)   | Uniform Refinement | `increment_start_rank`__     | candidate generation by advancement of        |
|                         | Approach           |                              | 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          |
+-------------------------+--------------------+------------------------------+-----------------------------------------------+

.. __: method-multifidelity_function_train-p_refinement-uniform-increment_start_rank.html
__ method-multifidelity_function_train-p_refinement-uniform-increment_start_order.html
__ method-multifidelity_function_train-p_refinement-uniform-increment_max_rank.html
__ method-multifidelity_function_train-p_refinement-uniform-increment_max_order.html
__ method-multifidelity_function_train-p_refinement-uniform-increment_max_rank_order.html



**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.