Package: SFOCDs 1.2.0

SFOCDs: Space Filling Optimal Covariate Designs

We have designed this package to address experimental scenarios involving multiple covariates. It focuses on construction of Optimal Covariate Designs (OCDs), checking space filling property of the developed design. The primary objective of the package is to generate OCDs using four methods viz., M array method, Juxtapose method, Orthogonal Integer Array and Hadamard method. The package also evaluates space filling properties of both the base design and OCDs using the MaxPro criterion, providing a meaningful basis for comparison. In addition, it includes tool to visualize the spread offered by the design points in the form of scatterplot, which help users to assess distribution and coverage of design points.

Authors:Neethu RS [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Ashutosh Dalal [aut, ctb, cre]

SFOCDs_1.2.0.tar.gz
SFOCDs_1.2.0.zip(r-4.7)SFOCDs_1.2.0.zip(r-4.6)SFOCDs_1.2.0.zip(r-4.5)
SFOCDs_1.2.0.tgz(r-4.6-any)SFOCDs_1.2.0.tgz(r-4.5-any)
SFOCDs_1.2.0.tar.gz(r-4.7-any)SFOCDs_1.2.0.tar.gz(r-4.6-any)
SFOCDs_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SFOCDs/json (API)

# Install 'SFOCDs' in R:
install.packages('SFOCDs', 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.

1.48 score 454 downloads 7 exports 0 dependencies

Last updated from:e9816a05eb. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK97
source / vignettesOK137
linux-release-x86_64OK103
macos-release-arm64OK116
macos-oldrel-arm64OK63
windows-develOK60
windows-releaseOK66
windows-oldrelOK62
wasm-releaseOK80

Exports:HadamardOCDsJuxtaOCDsMaxDotMaxpro_CriterionMOCDsOIAOCDsreshuffle_des

Dependencies: