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