# LHD v1.1.0

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## 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) | |

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## Vignettes of LHD

Name | ||

Vignette_for_LHD.Rmd | ||

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## Last month downloads

## Details

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 |

suggests | devtools , knitr , rmarkdown , testthat |

imports | stats |

Contributors | Hongzhi Wang, Qian Xiao, Abhyuday Mandal |

#### Include our badge in your README

```
[![Rdoc](http://www.rdocumentation.org/badges/version/LHD)](http://www.rdocumentation.org/packages/LHD)
```