optSeededLHS {lhs} | R Documentation |
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.
optSeededLHS(seed, m=1, maxSweeps=2, eps=.1)
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 |
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.
An n
by k
Latin Hypercube Sample matrix with values uniformly distributed on [0,1]
Rob Carnell
Stein, M. (1987) Large Sample Properties of Simulations Using Latin Hypercube Sampling. Technometrics. 29, 143–151.
randomLHS
, geneticLHS
,
improvedLHS
, maximinLHS
, and
optimumLHS
to generate Latin Hypercube Samples.
optAugmentLHS
and
augmentLHS
to modify and augment existing designs.
a <- randomLHS(4,3) a optSeededLHS(a, 2, 2, .1)