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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) <doi:10.48550/arXiv.2107.00728>.

Version: 1.0
Depends: R (≥ 2.10)
Imports: mvtnorm, MASS, philentropy
Published: 2023-02-22
Author: Xiaoping Shi ORCID iD [aut, cre]
Maintainer: Xiaoping Shi <xiaoping.shi at ubc.ca>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: GRelevance results

Documentation:

Reference manual: GRelevance.pdf

Downloads:

Package source: GRelevance_1.0.tar.gz
Windows binaries: r-devel: GRelevance_1.0.zip, r-release: GRelevance_1.0.zip, r-oldrel: GRelevance_1.0.zip
macOS binaries: r-release (arm64): GRelevance_1.0.tgz, r-oldrel (arm64): GRelevance_1.0.tgz, r-release (x86_64): GRelevance_1.0.tgz, r-oldrel (x86_64): GRelevance_1.0.tgz

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These binaries (installable software) and packages are in development.
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