Package: MOLHD 0.2

MOLHD: Multiple Objective Latin Hypercube Design

Generate the optimal maximin distance, minimax distance (only for low dimensions), and maximum projection designs within the class of Latin hypercube designs efficiently for computer experiments. Generate Pareto front optimal designs for each two of the three criteria and all the three criteria within the class of Latin hypercube designs efficiently. Provide criterion computing functions. References of this package can be found in Morris, M. D. and Mitchell, T. J. (1995) <doi:10.1016/0378-3758(94)00035-T>, Lu Lu and Christine M. Anderson-CookTimothy J. Robinson (2011) <doi:10.1198/Tech.2011.10087>, Joseph, V. R., Gul, E., and Ba, S. (2015) <doi:10.1093/biomet/asv002>.

Authors:Ruizhe Hou , Lu Lu

MOLHD_0.2.tar.gz
MOLHD_0.2.zip(r-4.7)MOLHD_0.2.zip(r-4.6)MOLHD_0.2.zip(r-4.5)
MOLHD_0.2.tgz(r-4.6-any)MOLHD_0.2.tgz(r-4.5-any)
MOLHD_0.2.tar.gz(r-4.7-any)MOLHD_0.2.tar.gz(r-4.6-any)
MOLHD_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
MOLHD/json (API)

# Install 'MOLHD' in R:
install.packages('MOLHD', repos = c('https://ruizhehou.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ruizhehou/molhd/issues

On CRAN:

Conda:

2.85 score 14 scripts 127 downloads 14 exports 10 dependencies

Last updated from:5e356fd51f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK122
source / vignettesOK183
linux-release-x86_64OK151
macos-release-arm64OK134
macos-oldrel-arm64OK144
windows-develOK81
windows-releaseOK76
windows-oldrelOK75
wasm-releaseOK99

Exports:cpf2cpf3LHDmdmiMmiMLHDMmMmLHDmpmpLHDpfMmpfMppfMpmpfpm

Dependencies:arrangementsdotCall64fieldsgmpmapsR6RColorBrewerRcppspamviridisLite