MmLHD: Generate the optimal Maximin Latin Hypercube Design.

In MOLHD: Multiple Objective Latin Hypercube Design

Description

Generate the optimal Maximin Latin Hypercube Design.

Usage

MmLHD(n, p, power = 100, temp0 = 0, nstarts = 1, times = 300,
  maxiter = 1e+06)

Arguments

n	number of runs desired
p	number of variables desired
power	Optional, default is "100". The power parameter r in the average reciprocal inter-point distance measure. When r turns to infinity, minimizing the average reciprocal inter-point distance measure is equivalent to maximizing the minimum distance among the design points.
temp0	Initial temperature
nstarts	Optional, default is "1". The number of random starts
times	Optional, default is "300". The maximum number of non-improving searches allowed. Lower this parameter if you expect the search to converge faster.
maxiter	Optional, default is "1e+06".The maximum total number of iterations for each random start. Lower this number if the design is prohibitively large and you want to terminate the algorithm prematurely to report the best design found

Details

This function is to search the optimal Maximin design using columnwise exchange algorithm coupled with the simulated annealing algorithm and several computational shortcuts to improve efficiency.

Value

design	The optimal Maximin design matrix
criterion	The opproximate Maximin criterion of the design under chosen "power" parameter
iterations	The total iterations
time_rec	Time to complete the search

Examples

#Generate the optimal maximin distance LHD(20,2)
D=MmLHD(n=20,p=2)
D$design
D$criterion

MOLHD documentation built on May 2, 2019, 8:38 a.m.