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Their paper ''An approach to sensitivity analysis of computer models, Part I. Introduction, input variable selection and preliminary variable assessment.'' appeared in the Journal of Quality Technology in [[1981]].
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.
When sampling a function of <math>N</math> variables, the range of each variable is divided into <math>M</math> different regions. <math>M</math> sample points are then placed to satisfy the Latin hypercube requirements; note that this forces the number of divisions, <math>M</math>, to be equal for each variable. Also note that this sampling scheme does not require more samples for more dimensions (variables); this independence is one of the main advantages of this sampling scheme.
[[Category:Statistics]]
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