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The [[statistics|statistical]] method of '''Latin hypercube sampling''' ('''LHS''') was developed to generate a distribution of plausible collections of parameter values from a [[multidimensional distribution]]. The [[Sampling (statistics)|sampling method]] is often applied in [[uncertainty]] analysis.
The technique was first described by McKay in 1979.<ref name = "C3M">{{cite journal
The technique was first described by McKay<ref>{{cite journal |last=McKay |first=M.D. |coauthors=Conover, W.J.; and Beckman, R.J. |title=A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code |year=1979 |journal=Technometrics |volume=21 |pages=239–245 |doi=10.2307/1268522}}</ref> in 1979. It was further elaborated by [[Ronald L. Iman]], and others<ref>{{cite journal |last=Iman |first=R.L. |coauthors=Helton, J.C.; and [[James Edward Campbell|Campbell, J.E.]] |title=An approach to sensitivity analysis of computer models, Part 1. Introduction, input variable selection and preliminary variable assessment |journal=Journal of Quality Technology |volume=13 |issue=3 |pages=174–183 |year=1981 }}</ref> in 1981. Detailed computer codes and manuals were later published.<ref>{{cite book |last=Iman |first=R.L. |coauthors=Davenport, J.M. ; Zeigler, D.K. |title=Latin hypercube sampling (program user's guide) |year=1980 |id={{OSTI|5571631}}}}</ref>▼
| last = McKay
| first = M.D.
| coauthors = Beckman, R.J.; Conover, W.J.
| year = 1979
| month = May
| title = A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
| journal = [[Technometrics]]
| volume = 21
| issue = 2
| pages = 239–245
| publisher = [[American Statistical Association]]
| issn = 0040-1706
| doi = 10.2307/1268522
| id = {{OSTI|5236110}}
| url = http://www.jstor.org/pss/1268522
| format = [[JSTOR]] Abstract
| accessdate = 2009-03-03
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In the context of statistical sampling, a square grid containing sample positions is a [[Latin square]] if (and only if) there is only one sample in each row and each column. A '''Latin hypercube''' is the generalisation of this concept to an arbitrary number of dimensions, whereby each sample is the only one in each axis-aligned hyperplane containing it.
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