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LHD (version 1.4.1)

Latin Hypercube Designs (LHDs)

Description

Contains different algorithms and construction methods for optimal Latin hypercube designs (LHDs) with flexible sizes. Our package is comprehensive since it is capable of generating maximin distance LHDs, maximum projection LHDs, and orthogonal and nearly orthogonal LHDs. Detailed comparisons and summary of all the algorithms and construction methods in this package can be found at Hongzhi Wang, Qian Xiao and Abhyuday Mandal (2021) . This package is particularly useful in the area of Design and Analysis of Experiments (DAE). More specifically, design of computer experiments.

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Version

Install

install.packages('LHD')

Monthly Downloads

293

Version

1.4.1

License

MIT + file LICENSE

Maintainer

Hongzhi Wang

Last Published

February 12th, 2025

Functions in LHD (1.4.1)

SA2008

Simulated Annealing for LHD with Multi-objective Optimization Approach
SA

Simulated Annealing for LHD
SLHD

Sliced Latin Hypercube Design (SLHD)
OLHD.S2010

Orthogonal Latin Hypercube Design
OLHD.Y1998

Orthogonal Latin Hypercube Design
WT

Williams Transformation
rLHD

Generate a random Latin Hypercube Design (LHD)
dij

Calculate the Inter-site Distance
phi_p

Calculate the phi_p Criterion
exchange

Exchange two random elements in a matrix
OLHD.C2007

Orthogonal Latin Hypercube Design
OLHD.L2009

Orthogonal Latin Hypercube Design
LaPSO

Particle Swarm Optimization for LHD
MaxProCriterion

Calculate the Maximum Projection Criterion
AvgAbsCor

Calculate the Average Absolute Correlation
OLHD.B2001

Orthogonal Latin Hypercube Design
MaxAbsCor

Calculate the Maximum Absolute Correlation
OA2LHD

Transfer an Orthogonal Array (OA) into an LHD
GLP

Good Lattice Point Design
FastMmLHD

Fast Maximin Distance LHD
GA

Genetic Algorithm for LHD
OASA

Orthogonal-Array-Based Simulated Annealing