Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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sample_type


Selection of sampling strategy

Specification

Alias: none

Argument(s): none

Default: lhs

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Required
(Choose One)
Group 1 lhs

Uses Latin Hypercube Sampling (LHS) to sample variables

random

Uses purely random Monte Carlo sampling to sample variables

Description

The sample_type keyword allows the user to select between two types of sampling: Monte Carlo (pure random) and Latin hypercube (stratified) sampling.

The incremental keywords are deprecated; instead use samples together with refinement_samples.

Default Behavior

If the sample_type keyword is present, it must be accompanied by lhs or random. In most contexts, lhs is the default (exception: multilevel_sampling uses Monte Carlo by default).

Examples

method
  sampling
    sample_type lhs
    samples = 20
    seed = 83921