lhs
Uses Latin Hypercube Sampling (LHS) to sample variables
Specification
Alias: None
Arguments: None
Description
The lhs
keyword invokes Latin Hypercube Sampling as the means of
drawing samples of uncertain variables according to their probability
distributions. This is a stratified, space-filling approach that
selects variable values from a set of equi-probable bins.
Default Behavior
Latin Hypercube Sampling is the default sampling mode in most contexts
(exception: multilevel_sampling). To explicitly specify LHS in the
Dakota input file, the lhs
keyword must appear in conjunction with
the sample_type
keyword.
Usage Tips
Latin Hypercube Sampling is very robust and can be applied to any problem. It is fairly effective at estimating the mean of model responses and linear correlations with a reasonably small number of samples relative to the number of variables.
Examples
method
sampling
sample_type lhs
samples = 20