uniformLHD: Generate a uniform Latin-hypercube design (LHD)

In SFDesign: Space-Filling Designs

Generate a uniform Latin-hypercube design (LHD)

Description

This function generates a uniform LHD by minimizing the wrap-around discrepancy.

Usage

uniformLHD(
  n,
  p,
  design = NULL,
  max.sa.iter = 1e+06,
  temp = 0,
  decay = 0.95,
  no.update.iter.max = 400,
  num.passes = 10,
  max.det.iter = 1e+06,
  method = "full",
  scaled = TRUE
)

Arguments

n	design size.
p	design dimension.
design	an initial LHD. If design=NULL, a random LHD is generated.
max.sa.iter	maximum number of swapping involved in the simulated annealing (SA) algorithm.
temp	initial temperature of the simulated annealing algorithm. If temp=0, it will be automatically determined.
decay	the temperature decay rate of simulated annealing.
no.update.iter.max	the maximum number of iterations where there is no update to the global optimum before SA stops.
num.passes	the maximum number of passes of the whole design matrix if deterministic swapping is used.
max.det.iter	maximum number of swapping involved in the deterministic swapping algorithm.
method	choice of "deterministic", "sa", or "full". If the method="full", the design is first optimized by SA and then deterministic swapping.
scaled	whether the design is scaled to unit hypercube. If scaled=FALSE, the design is represented by integer numbers from 1 to design size. Leave it as TRUE when no initial design is provided.

Details

uniformLHD generates a uniform LHD minimizing wrap-around discrepancy (see uniform.crit). The optimization details can be found in customLHD.

Value

design	final design points.
total.iter	total number of swaps in the optimization.
criterion	final optimized criterion.
crit.hist	criterion history during the optimization process.

Examples

n = 20
p = 3
D = uniformLHD(n, p)

SFDesign documentation built on June 22, 2025, 1:06 a.m.