Package: PAFit 1.2.11

Thong Pham

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>. Thong Pham et al. (2020) <doi:10.18637/jss.v092.i03>. Thong Pham et al. (2021) <doi:10.1093/comnet/cnab024>.

Authors:Thong Pham [aut, cre], Paul Sheridan [aut], Hidetoshi Shimodaira [aut]

PAFit_1.2.11.tar.gz
PAFit_1.2.11.tar.gz(r-4.7-arm64)PAFit_1.2.11.tar.gz(r-4.7-x86_64)PAFit_1.2.11.tar.gz(r-4.6-arm64)PAFit_1.2.11.tar.gz(r-4.6-x86_64)
PAFit_1.2.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PAFit/json (API)
NEWS

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

Bug tracker:https://github.com/thongphamthe/pafit/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • coauthor.author_id - A collaboration network between authors of papers in the field of complex networks with article time-stamps
  • coauthor.net - A collaboration network between authors of papers in the field of complex networks with article time-stamps
  • coauthor.truetime - A collaboration network between authors of papers in the field of complex networks with article time-stamps

On CRAN:

Conda:

cppopenmp

3.54 score 70 scripts 588 downloads 5 mentions 22 exports 51 dependencies

Last updated from:1cc804e527. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK198
linux-devel-x86_64OK212
source / vignettesOK219
linux-release-arm64OK187
linux-release-x86_64OK210
wasm-releaseOK124

Exports:as.PAFit_netfrom_igraphfrom_networkDynamicgenerate_BAgenerate_BBgenerate_ERgenerate_fit_onlygenerate_netgenerate_simulated_data_from_estimated_modelget_statisticsgraph_from_filegraph_to_fileJeongjoint_estimateNewmanonly_A_estimateonly_F_estimatePAFit_oneshotplot_contributiontest_linear_PAto_igraphto_networkDynamic

Dependencies:celestialclicodacpp11dplyrevaluatefarvergenericsggplot2gluegtablehighrigraphisobandknitrlabelinglatticelifecyclemagicaxismagrittrmapprojmapsMASSMatrixnetworknetworkDynamicnetworkLiteNISTunitspillarpkgconfigplotrixplyrpracmaR6RANNRColorBrewerRcpprlangS7scalessmstatnet.commontibbletidyselectutf8vctrsVGAMviridisLitewithrxfunyaml

PAFit: an R Package for the Non-Parametric Estimation of Preferential Attachment and Node Fitness in Temporal Complex Networks

Rendered fromTutorial.pdf.asisusingR.rsp::asison Jun 04 2026.

Last update: 2018-09-19
Started: 2015-03-27

Readme and manuals

Help Manual

Help pageTopics
Generative Mechanism Estimation in Temporal Complex NetworksPAFit-package PAFit
Converting an edgelist matrix to a PAFit_net objectas.PAFit_net
A collaboration network between authors of papers in the field of complex networks with article time-stampscoauthor.author_id coauthor.net coauthor.truetime ComplexNetCoauthor
Convert an igraph object to a PAFit_net objectfrom_igraph
Convert a networkDynamic object to a PAFit_net objectfrom_networkDynamic
Simulating networks from the generalized Barabasi-Albert modelgenerate_BA
Simulating networks from the Bianconi-Barabasi modelgenerate_BB
Simulating networks from the Erdos-Renyi modelgenerate_ER
Simulating networks from the Caldarelli modelgenerate_fit_only
Simulating networks from preferential attachment and fitness mechanismsgenerate_net
Generating simulated data from a fitted modelgenerate_simulated_data_from_estimated_model
Getting summarized statistics from input dataget_statistics PAFit_data
Read file to a PAFit_net objectgraph_from_file
Write the graph in a PAFit_net object to filegraph_to_file
Jeong's method for estimating the preferential attachment functionJeong
Joint inference of attachment function and node fitnessesjoint_estimate
Corrected Newman's method for estimating the preferential attachment functionNewman
Estimating the attachment function in isolation by PAFit methodonly_A_estimate
Estimating node fitnesses in isolationonly_F_estimate
Estimating the nonparametric preferential attachment function from one single snapshot.PAFit_oneshot
Plotting contributions calculated from the observed data and contributions calculated from simulated dataplot_contribution
Plotting the estimated attachment function and node fitnessplot.Full_PAFit_result
Plotting the estimated attachment functionplot.PA_result
Plot a 'PAFit_net' objectplot.PAFit_net
Plotting the estimated attachment function and node fitness of a 'PAFit_result' objectplot.PAFit_result
Printing simple information of the cross-validation dataprint.CV_Data
Printing simple information of the cross-validation resultprint.CV_Result
printing information on the estimation resultprint.Full_PAFit_result
Printing information of the estimated attachment functionprint.PA_result
Printing simple information on the statistics of the network stored in a 'PAFit_data' objectprint.PAFit_data
Printing simple information of a 'PAFit_net' objectprint.PAFit_net
printing information on the estimation result stored in a 'PAFit_result' objectprint.PAFit_result
Printing summary information of the cross-validation datasummary.CV_Data
Output summary information of the cross-validation resultsummary.CV_Result
Summary information on the estimation resultsummary.Full_PAFit_result
Summary of the estimated attachment functionsummary.PA_result
Output summary information on the statistics of the network stored in a 'PAFit_data' objectsummary.PAFit_data
Summary information of a 'PAFit_net' objectsummary.PAFit_net
Output summary information on the estimation result stored in a 'PAFit_result' objectsummary.PAFit_result
Fitting various distributions to a degree vectortest_linear_PA
Convert a PAFit_net object to an igraph objectto_igraph
Convert a PAFit_net object to a networkDynamic objectto_networkDynamic