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Dakota Reference Manual
Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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Allow refinement of probability and generalized reliability results using importance sampling
This keyword is related to the topics:
Alias: sample_refinement
Argument(s): none
Default: no refinement
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Required (Choose One) | Group 1 | import | Sampling option | |
adapt_import | Importance sampling option | |||
mm_adapt_import | Sampling option | |||
Optional | refinement_samples | Number of samples used to refine a probabilty estimate or sampling design. |
The probability_refinement
allows refinement of probability and generalized reliability results using importance sampling. If one specifies probability_refinement
, there are some additional options. One can specify which type of importance sampling to use (import
, adapt_import
, or mm_adapt_import
). Additionally, one can specify the number of refinement samples to use with refinement_samples
and the seed to use with seed
.
The probability_refinement
density reweighting accounts originally was developed based on Gaussian distributions. It now accounts for additional non-Gaussian cases.