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LHD (version 1.3.3)

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

267

Version

1.3.3

License

MIT + file LICENSE

Maintainer

Hongzhi Wang

Last Published

July 31st, 2021

Functions in LHD (1.3.3)

AvgAbsCor

Calculate the Average Absolute Correlation
SLHD

Sliced Latin Hypercube Design (SLHD)
WT

Williams Transformation
GLP

Good Lattice Point Design
SA2008

Simulated Annealing for LHD with Multi-objective Optimization Approach
OLHD.B2001

Orthogonal Latin Hypercube Design
OASA

Orthogonal-Array-Based Simulated Annealing
OA2LHD

Transfer an Orthogonal Array (OA) into an LHD
OLHD.Y1998

Orthogonal Latin Hypercube Design
OLHD.S2010

Orthogonal Latin Hypercube Design
dij

Calculate the Inter-site Distance
exchange

Exchange two random elements in a matrix
FastMmLHD

Fast Maximin Distance LHD
MaxAbsCor

Calculate the Maximum Absolute Correlation
phi_p

Calculate the phi_p Criterion
rLHD

Generate a random Latin Hypercube Design (LHD)
OLHD.C2007

Orthogonal Latin Hypercube Design
OLHD.L2009

Orthogonal Latin Hypercube Design
LaPSO

Particle Swarm Optimization for LHD
GA

Genetic Algorithm for LHD
SA

Simulated Annealing for LHD
MaxProCriterion

Calculate the Maximum Projection Criterion