Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
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sample_type


Selection of sampling strategy

Specification

Alias: none

Argument(s): none

Default: lhs

Child Keywords:

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

Uses Latin Hypercube Sampling (LHS) to sample variables

random

Uses purely random Monte Carlo sampling to sample variables

incremental_lhs

(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study

incremental_random

(Deprecated keyword) Augments an existing random sampling study

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