LHD v1.1.0


Monthly downloads



Latin Hypercube Designs (LHDs) Algorithms

Contains different algorithms for efficient Latin Hypercube Designs (LHDs) with flexible sizes. Our package is comprehensive since it is capable of generating nearly orthogonal LHDs, maximin distance LHDs, and maximum projection LHDs. Documentation for each algorithm includes useful information and explanation along with corresponding references. This package is particularly useful in the area of Design and Analysis of Experiments (DAE). More specifically, design of computer experiments.

Functions in LHD

Name Description
SA2008 Simulated Annealing for LHD with Multi-objective Optimization Approach
OASA Orthogonal-Array-Based Simulated Annealing
SLHD Sliced Latin Hypercube Design (SLHD)
GA Genetic Algorithm for LHD
MaxAbsCor Calculate the Maximum Absolute Correlation
AvgAbsCor Calculate the Average Absolute Correlation
LaPSO Particle Swarm Optimization for LHD
phi_p Calculate the phi_p Criterion
SA Simulated Annealing for LHD
MaxProCriterion Calculate the Maximum Projection Criterion
dij Calculate the Inter-site Distance
exchange Exchange two random elements
OA2LHD Transfer an Orthogonal Array (OA) into an LHD
rLHD Generate a random Latin Hypercube Design (LHD)
No Results!

Vignettes of LHD

No Results!

Last month downloads


Type Package
License MIT + file LICENSE
Encoding UTF-8
LazyData true
RoxygenNote 7.1.0
VignetteBuilder knitr
NeedsCompilation no
Packaged 2020-06-02 02:50:45 UTC; wangh
Repository CRAN
Date/Publication 2020-06-02 04:30:02 UTC

Include our badge in your README