PAFit: Generative Mechanism Estimation in Temporal Complex Networks

Statistical methods for estimating preferential attachment and node fitness generative mechanisms in temporal complex networks are provided. Thong Pham et al. (2015) <doi:10.1371/journal.pone.0137796>. Thong Pham et al.(2016) <doi:10.1038/srep32558>.

Version: 1.0.0.7
Depends: R (≥ 2.10.0)
Imports: Rcpp (≥ 0.11.3) , grDevices, graphics, stats, RColorBrewer, VGAM, MASS, magicaxis, networkDynamic, network, plyr, igraph, mapproj, knitr
LinkingTo: Rcpp
Suggests: R.rsp
Published: 2018-09-19
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongpham at thongpham.net>
BugReports: https://github.com/thongphamthe/PAFit/issues
License: GPL-3
URL: https://github.com/thongphamthe/PAFit
NeedsCompilation: yes
Citation: PAFit citation info
Materials: NEWS
In views: SocialSciences
CRAN checks: PAFit results

Downloads:

Reference manual: PAFit.pdf
Vignettes: PAFit: an R Package for the Non-Parametric Estimation of Preferential Attachment and Node Fitness in Temporal Complex Networks
Package source: PAFit_1.0.0.7.tar.gz
Windows binaries: r-devel: PAFit_1.0.0.7.zip, r-release: PAFit_1.0.0.7.zip, r-oldrel: PAFit_1.0.0.6.zip
OS X binaries: r-release: PAFit_1.0.0.6.tgz, r-oldrel: PAFit_1.0.0.6.tgz
Old sources: PAFit archive

Reverse dependencies:

Reverse imports: mcPAFit

Linking:

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