Dakota Reference Manual
Version 6.4
LargeScale Engineering Optimization and Uncertainty Analysis

Samples variables on full factorial grid of study points
This keyword is related to the topics:
Alias: none
Argument(s): INTEGERLIST
Dakota's multidimensional parameter study computes response data sets for an ndimensional grid of points. Each continuous and discrete range variable is partitioned into equally spaced intervals between its upper and lower bounds, each discrete set variable is partitioned into equally spaced index intervals. The partition boundaries in ndimensional space define a grid of points, and every point is evaluated.
Default Behavior
By default, the multidimensional parameter study operates over all types of variables.
Expected Outputs
A multidimensional parameter study produces a set of responses for each parameter set that is generated.
Usage Tips
Since the initial values from the variables specification will not be used, they need not be specified.
This example is taken from the Users Manual and is a good comparison to the examples on centered_parameter_study and vector_parameter_study.
# tested on Dakota 6.0 on 140501 environment tabular_data tabular_data_file = 'rosen_multidim.dat' method multidim_parameter_study partitions = 10 8 model single variables continuous_design = 2 lower_bounds 2.0 2.0 upper_bounds 2.0 2.0 descriptors 'x1' "x2" interface analysis_driver = 'rosenbrock' fork responses response_functions = 1 no_gradients no_hessians
This example illustrates the full factorial combinations of parameter values created by the multidim_parameter_study. With 10 and 8 partitions, there are actually 11 and 9 values for each variable. This means that function evaluations will be required.
These keywords may also be of interest: