optSeededLHS: Optimum Seeded Latin Hypercube Sample

In lhs: Latin Hypercube Samples

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

optSeededLHS(seed, m = 0, maxSweeps = 2, eps = 0.1, verbose = FALSE)

Arguments

seed	The number of partitions (simulations or design points)
m	The number of additional points to add to the seed matrix seed. default value is zero. If m is zero then the seed design is optimized.
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]

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

  set.seed(1234)
  a <- randomLHS(4,3)
  b <- optSeededLHS(a, 2, 2, .1)

lhs documentation built on July 1, 2024, 1:06 a.m.