![]() The problem is that it wouldn’t be uniform sampleĪcross the range. Latin Hypercube Sampling Latin Hypercube sampling is a recent development in sampling technology designed to accurately recreate the input distribution through sampling in fewer iterations when compared with the Monte Carlo method. Examples of (a) random sampling, (b) full factorial sampling, and (c) Latin hypercube sampling, for a simple case of 10 samples (samples for U (6,10) and N (0.4, 0.1) are shown).In random. Points, then you could divide up the range into three almostĮqual parts and sample from 1:3, 4:6, andħ:10. Description example X lhsdesign (n,p) returns a Latin hypercube sample matrix of size n -by- p. ![]() If you want integers only in the sample, then we must be carefulĪbout what we mean by a Latin hypercube sample. LHS was written for the generation of multivariate samples either completely at random or by a constrained randomization termed Latin hypercube sampling (LHS).
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