Dakota Reference Manual  Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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centered_parameter_study

Samples variables along points moving out from a center point

Topics

This keyword is related to the topics:

Specification

Alias: none

Argument(s): none

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Required step_vector

Size of steps to be taken in each dimension of a centered parameter study

Required steps_per_variable

Number of steps to take in each dimension of a centered parameter study

Optional model_pointer

Identifier for model block to be used by a method

Description

Dakota's centered parameter study computes response data sets along multiple coordinate-based vectors, one per parameter, centered about the initial values from the variables specification. This is useful for investigation of function contours with respect to each parameter individually in the vicinity of a specific point (e.g., post-optimality analysis for verification of a minimum), thereby avoiding the cost associated with a multidimensional grid.

Default Behavior

By default, the centered parameter study operates over all types of variables.

The centered_parameter_study takes steps along each orthogonal dimension. Each dimension is treated independently. The number of steps are taken in each direction, so that the total number of points in the parameter study is $1+ 2\sum{n} $.

Expected Outputs

A centered parameter study produces a set of responses for each parameter set that is generated.

Examples

The following example is a good comparison to the examples on multidim_parameter_study and vector_parameter_study.

# tested on Dakota 6.0 on 140501
environment
  tabular_data
    tabular_data_file = 'rosen_centered.dat'

method
  centered_parameter_study
    steps_per_variable = 5 4
    step_vector = 0.4 0.5

model
  single

variables
  continuous_design = 2
    initial_point =   0        0
    descriptors =     'x1'     "x2"

interface
  analysis_driver = 'rosenbrock'
    fork

responses
  response_functions = 1
  no_gradients
  no_hessians

See Also

These keywords may also be of interest: