Dakota Reference Manual: parameter_studies

| Dakota Reference Manual Version 6.15 Explore and Predict with Confidence

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## Description

Parameter studies employ deterministic designs to explore the effect of parametric changes within simulation models, yielding one form of sensitivity analysis. They can help assess simulation characteristics such as smoothness, multi-modality, robustness, and nonlinearity, which affect the choice of algorithms and controls in follow-on optimization and UQ studies.

Dakota's parameter study methods compute response data sets at a selection of points in the parameter space. These points may be specified as a vector, a list, a set of centered vectors, or a multi-dimensional grid. Capability overviews and examples of the different types of parameter studies are provided in the Users Manual [4].

With the exception of output verbosity (a setting of `silent` will suppress some parameter study diagnostic output), Dakota's parameter study methods do not make use of the method independent controls. Therefore, the parameter study documentation which follows is limited to the method dependent controls for the vector, list, centered, and multidimensional parameter study methods.

## Related Topics

## Related Keywords

- centered_parameter_study : Samples variables along points moving out from a center point
- list_parameter_study : Samples variables as a specified values
- multidim_parameter_study : Samples variables on full factorial grid of study points
- partitions : Samples variables on full factorial grid of study points
- vector_parameter_study : Samples variables along a user-defined vector