Optimal Augmented Latin Hypercube Sample

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Description

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function attempts to add the points to the design in an optimal way.

Usage

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optAugmentLHS(lhs, m=1, mult=2)

Arguments

lhs

The Latin Hypercube Design to which points are to be added

m

The number of additional points to add to matrix lhs

mult

m*mult random candidate points will be created.

Details

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function attempts to add the points to the design in a way that maximizes S optimality.

S-optimality seeks to maximize the mean distance from each design point to all the other points in the design, so the points are as spread out as possible.

Value

An n by k Latin Hypercube Sample matrix with values uniformly distributed on [0,1]

Author(s)

Rob Carnell

References

Stein, M. (1987) Large Sample Properties of Simulations Using Latin Hypercube Sampling. Technometrics. 29, 143–151.

See Also

randomLHS, geneticLHS, improvedLHS, maximinLHS, and optimumLHS to generate Latin Hypercube Samples. optSeededLHS and augmentLHS to modify and augment existing designs.

Examples

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  a <- randomLHS(4,3)
  a
  optAugmentLHS(a, 2, 3)