CooccurrenceAffinity: Affinity in Co-Occurrence Data

Computes a novel metric of affinity between two entities based on their co-occurrence (using binary presence/absence data). The metric and its MLE, alpha hat, were advanced in Mainali, Slud, et al, 2021 <doi:10.1126/sciadv.abj9204>. Various types of confidence intervals and median interval were developed in Mainali and Slud, 2022 <doi:10.1101/2022.11.01.514801>.

Version: 1.0
Depends: R (≥ 4.1), BiasedUrn (≥ 2.0.9)
Imports: cowplot, ggplot2, plyr, reshape
Suggests: cooccur
Published: 2023-05-03
Author: Kumar Mainali [aut, cre], Eric Slud [aut]
Maintainer: Kumar Mainali <kpmainali at gmail.com>
BugReports: https://github.com/kpmainali/CooccurrenceAffinity/issues
License: MIT + file LICENSE
URL: https://github.com/kpmainali/CooccurrenceAffinity
NeedsCompilation: no
Materials: README
CRAN checks: CooccurrenceAffinity results

Documentation:

Reference manual: CooccurrenceAffinity.pdf

Downloads:

Package source: CooccurrenceAffinity_1.0.tar.gz
Windows binaries: r-prerel: CooccurrenceAffinity_1.0.zip, r-release: CooccurrenceAffinity_1.0.zip, r-oldrel: CooccurrenceAffinity_1.0.zip
macOS binaries: r-prerel (arm64): CooccurrenceAffinity_1.0.tgz, r-release (arm64): CooccurrenceAffinity_1.0.tgz, r-oldrel (arm64): CooccurrenceAffinity_1.0.tgz, r-prerel (x86_64): CooccurrenceAffinity_1.0.tgz, r-release (x86_64): CooccurrenceAffinity_1.0.tgz

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