Package: Perc 0.1.6

Jessica Vandeleest

Perc: Using Percolation and Conductance to Find Information Flow Certainty in a Direct Network

To find the certainty of dominance interactions with indirect interactions being considered.

Authors:Kevin Fujii [aut], Jian Jin [aut], Jessica Vandeleest [aut, cre], Aaron Shev [aut], Brianne Beisner [aut], Brenda McCowan [aut, cph], Hsieh Fushing [aut, cph]

Perc_0.1.6.tar.gz
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Perc.pdf |Perc.html✨
Perc/json (API)

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

Bug tracker:https://github.com/hanettools/perc/issues

Datasets:

On CRAN:

Conda:

5.88 score 38 scripts 237 downloads 13 mentions 13 exports 0 dependencies

Last updated from:239c3f6555. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK135
source / vignettesOK178
linux-release-x86_64OK132
macos-release-arm64OK120
macos-oldrel-arm64OK210
windows-develOK103
windows-releaseOK105
windows-oldrelOK77
wasm-releaseOK105

Exports:as.conflictmatbradleyTerrybt.testconductancecountPathsdyadicLongConverterfindAllPathsfindIDpathsindividualDomProbplotConfmatsimRankOrdertransitivityvalueConverter

Dependencies:

Introduction to Perc Package

Fushing Lab & McCowan Lab, University of California, Davis

Rendered fromPerc.Rmdusingknitr::rmarkdownon Apr 10 2026.

Last update: 2020-04-27
Started: 2015-08-04