optAugmentLHS: Optimal Augmented 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 attempts to
add the points to the design in an optimal way.
Usage
optAugmentLHS(lhs, m = 1, mult = 2)
Value
An n by k Latin Hypercube Sample matrix with values uniformly distributed on [0,1]
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.
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.