Package: CompExpDes 1.0.9

CompExpDes: Designs for Computer Experimentations

In computer experiments space-filling designs are having great impact. Most popularly used space-filling designs are Uniform designs (UDs), Latin hypercube designs (LHDs) etc. For further references one can see Mckay (1979) <doi:10.1080/00401706.1979.10489755> and Fang (1980) <https://cir.nii.ac.jp/crid/1570291225616774784>. In this package, we have provided algorithms for generate efficient LHDs and UDs. Here, generated LHDs are efficient as they possess lower value of Maxpro measure, Phi_p value and Maximum Absolute Correlation (MAC) value based on the weightage given to each criterion. On the other hand, the produced UDs are having good space-filling property as they always attain the lower bound of Discrete Discrepancy measure. Further, some useful functions added in this package for adding more value to this package.

Authors:Ashutosh Dalal [aut, cre], Cini Varghese [aut, ctb], Rajender Parsad [aut, ctb], Mohd Harun [aut, ctb]

CompExpDes_1.0.9.tar.gz
CompExpDes_1.0.9.zip(r-4.7)CompExpDes_1.0.9.zip(r-4.6)CompExpDes_1.0.9.zip(r-4.5)
CompExpDes_1.0.9.tgz(r-4.6-any)CompExpDes_1.0.9.tgz(r-4.5-any)
CompExpDes_1.0.9.tar.gz(r-4.7-any)CompExpDes_1.0.9.tar.gz(r-4.6-any)
CompExpDes_1.0.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
CompExpDes/json (API)

# Install 'CompExpDes' in R:
install.packages('CompExpDes', repos = c('https://ashutoshdalal97.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.53 score 17 scripts 246 downloads 14 exports 0 dependencies

Last updated from:0bb4758b3f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK104
source / vignettesOK145
linux-release-x86_64OK114
macos-release-arm64OK109
macos-oldrel-arm64OK91
windows-develOK81
windows-releaseOK79
windows-oldrelOK152
wasm-releaseOK125

Exports:Best_ModelDiscrete_DiscrepancyMACmax_coincidence_numberMaxpro_MeasureNOLHDsOLHDs_2FPhipMeasureSLHDsUDesigns_IUDesigns_IIUDesigns_IIIwtLHDswtLHDs_prime

Dependencies: