influential: Identification of the Most Influential Nodes

Contains functions for reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: igraph, centiserve
Suggests: Hmisc (≥ 4.3-0), mgcv (≥ 1.8-31), nortest (≥ 1.0-4), NNS (≥ 0.4.7.1), parallel, knitr, rmarkdown
Published: 2020-04-25
Author: Adrian (Abbas) Salavaty
Maintainer: Adrian Salavaty <abbas.salavaty at gmail.com>
BugReports: http://github.com/asalavaty/influential/issues
License: GPL-3
URL: http://github.com/asalavaty/influential
NeedsCompilation: no
Citation: influential citation info
Materials: README NEWS
CRAN checks: influential results

Downloads:

Reference manual: influential.pdf
Vignettes: influential vignettes
Package source: influential_1.0.0.tar.gz
Windows binaries: r-devel: influential_1.0.0.zip, r-release: influential_1.0.0.zip, r-oldrel: influential_1.0.0.zip
macOS binaries: r-release: influential_1.0.0.tgz, r-oldrel: influential_1.0.0.tgz
Old sources: influential archive

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