Learn R Programming

⚠️There's a newer version (1.4.1) of this package.Take me there.

LHD (version 1.3.0)

Latin Hypercube Designs (LHDs)

Description

Contains different algorithms and construction methods for efficient 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. 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.

Copy Link

Version

Install

install.packages('LHD')

Monthly Downloads

203

Version

1.3.0

License

MIT + file LICENSE

Maintainer

Hongzhi Wang

Last Published

November 9th, 2020

Functions in LHD (1.3.0)

MaxProCriterion

Calculate the Maximum Projection Criterion
GLP

Good Lattice Point Design
MaxAbsCor

Calculate the Maximum Absolute Correlation
AvgAbsCor

Calculate the Average Absolute Correlation
OA2LHD

Transfer an Orthogonal Array (OA) into an LHD
WT

Williams Transformation
MWT

Modified Williams Transformation
OLHD2010

Orthogonal Latin Hypercube Design
SA

Simulated Annealing for LHD
OLHD1998

Orthogonal Latin Hypercube Design
dij

Calculate the Inter-site Distance
rLHD

Generate a random Latin Hypercube Design (LHD)
OLHD2001

Orthogonal Latin Hypercube Design
SA2008

Simulated Annealing for LHD with Multi-objective Optimization Approach
SLHD

Sliced Latin Hypercube Design (SLHD)
OASA

Orthogonal-Array-Based Simulated Annealing
OLHD2009

Orthogonal Latin Hypercube Design
phi_p

Calculate the phi_p Criterion
exchange

Exchange two random elements
OLHD2007

Orthogonal Latin Hypercube Design
LPWT

Linear Permuted Williams Transformation
GA

Genetic Algorithm for LHD
LOO

Leave-one-out Method
FastMmLHD

Fast Maximin Distance LHD
LaPSO

Particle Swarm Optimization for LHD