Optimum Seeded Latin Hypercube Sample

Description

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function then uses the columnwise pairwise (CP) algoritm to optimize the design. The original design is not necessarily maintained.

Usage

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optSeededLHS(seed, m=1, maxSweeps=2, eps=.1, verbose=FALSE)

Arguments

seed

The number of partitions (simulations or design points)

m

The number of additional points to add to matrix seed

maxSweeps

The maximum number of times the CP algorithm is applied to all the columns.

eps

The optimal stopping criterion

verbose

Print informational messages

Details

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function then uses the CP algoritm to optimize the design. The original design is not necessarily maintained.

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. optAugmentLHS and augmentLHS to modify and augment existing designs.

Examples

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  a <- randomLHS(4,3)
  a
  optSeededLHS(a, 2, 2, .1)