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Dakota Reference Manual
Version 6.16
Explore and Predict with Confidence
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Design and Analysis of Computer Experiments
This keyword is related to the topics:
Alias: none
Argument(s): none
Child Keywords:
| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
|---|---|---|---|---|
| Required (Choose One) | DACE type (Group 1) | grid | Grid Sampling | |
| random | Uses purely random Monte Carlo sampling to sample variables | |||
| oas | Orthogonal Array Sampling | |||
| lhs | Uses Latin Hypercube Sampling (LHS) to sample variables | |||
| oa_lhs | Orthogonal Array Latin Hypercube Sampling | |||
| box_behnken | Box-Behnken Design | |||
| central_composite | Central Composite Design | |||
| Optional | samples | Number of samples for sampling-based methods | ||
| Optional | seed | Seed of the random number generator | ||
| Optional | fixed_seed | Reuses the same seed value for multiple random sampling sets | ||
| Optional | main_effects | ANOVA | ||
| Optional | quality_metrics | Calculate metrics to assess the quality of quasi-Monte Carlo samples | ||
| Optional | variance_based_decomp | Activates global sensitivity analysis based on decomposition of response variance into contributions from variables | ||
| Optional | symbols | Number of replications in the sample set | ||
| Optional | model_pointer | Identifier for model block to be used by a method | ||
The Distributed Design and Analysis of Computer Experiments (DDACE) library provides the following DACE techniques:
grid)random)oas)lhs)oa_lhs)box_behnken)central_composite)These methods all generate point sets that may be used to drive a set of computer experiments. Note that all of the DACE methods generated randomized designs, except for Box-Behnken and Central composite which are classical designs. That is, the grid sampling will generate a randomized grid, not what one typically thinks of as a grid of uniformly spaced points over a rectangular grid. Similar, the orthogonal array is a randomized version of an orthogonal array: it does not generate discrete, fixed levels.
In addition to the selection of the method, there are keywords that affect the method outputs:
And keywords that affect the sampling:
These keywords may also be of interest: