Package: GRelevance 1.0

GRelevance: Graph-Based k-Sample Comparisons and Relevance Analysis in High Dimensions

We propose two distribution-free test statistics based on between-sample edge counts and measure the degree of relevance by standardized counts. Users can set edge costs in the graph to compare the parameters of the distributions. Methods for comparing distributions are as described in: Xiaoping Shi (2021) <arxiv:2107.00728>.

Authors:Xiaoping Shi [aut, cre]

GRelevance_1.0.tar.gz
GRelevance_1.0.zip(r-4.7)GRelevance_1.0.zip(r-4.6)GRelevance_1.0.zip(r-4.5)
GRelevance_1.0.tgz(r-4.6-any)GRelevance_1.0.tgz(r-4.5-any)
GRelevance_1.0.tar.gz(r-4.7-any)GRelevance_1.0.tar.gz(r-4.6-any)
GRelevance_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GRelevance/json (API)

# Install 'GRelevance' in R:
install.packages('GRelevance', repos = c('https://xshi1.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.

1.00 score 197 downloads 6 exports 7 dependencies

Last updated from:9f1a4df7cd. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK105
source / vignettesOK143
linux-release-x86_64OK104
macos-release-arm64OK135
macos-oldrel-arm64OK161
windows-develOK71
windows-releaseOK84
windows-oldrelOK57
wasm-releaseOK95

Exports:compbypathHpathMpermutpath.kruskalWeightWpermut

Dependencies:KernSmoothMASSmvtnormphilentropypoormanRcppRcppParallel