PAFit: Modelling and Inferencing Attachment Mechanisms of Temporal Complex Networks

A framework for modelling and inferencing attachment mechanisms of temporal complex networks is implemented in this package. For estimating the preferential attachment (PA) function in isolation, we implement Jeong's method, the corrected Newman's method and the PAFit method. For jointly estimating the PA function and node fitnesses, we implement the PAFit method. The package also provides flexible methods to generate a wide range of temporal networks based on PA and fitness.

AuthorThong Pham, Paul Sheridan, Hidetoshi Shimodaira
Date of publication2017-03-13 11:46:50
MaintainerThong Pham <thongpham@thongpham.net>
LicenseGPL-3
Version0.9.8.3
https://github.com/thongphamthe/PAFit

View on CRAN

Functions

GenerateNet Man page
GetStatistics Man page
PAFit Man page
PAFit_data Man page
PAFit_new Man page
PAFit-package Man page
plot.PAFit_result Man page
print.CV_Data Man page
print.CV_Result Man page
print.PAFit_data Man page
print.PAFit_result Man page
print.PA_result Man page
summary.CV_Data Man page
summary.CV_Result Man page
summary.PAFit_data Man page
summary.PAFit_result Man page
summary.PA_result Man page

Files

PAFit
PAFit/inst
PAFit/inst/simdata
PAFit/inst/simdata/true-fitness.txt
PAFit/inst/simdata/data2.txt
PAFit/inst/simdata/data1.txt
PAFit/inst/CITATION
PAFit/inst/NEWS.Rd
PAFit/inst/doc
PAFit/inst/doc/Tutorial.pdf.asis
PAFit/inst/doc/Tutorial.pdf
PAFit/tests
PAFit/tests/test_Newman_Kong.R
PAFit/tests/test_variance_s.R
PAFit/tests/test_overall.R
PAFit/tests/test_PAFit_log_linear.R
PAFit/tests/test_GetStatistics_compress_2.R
PAFit/tests/test_PA_only_f.R
PAFit/tests/test_GenerateNet_final_padding.R
PAFit/tests/test_PAFit.R
PAFit/tests/loop_overall.R
PAFit/tests/loop_PAFit.R
PAFit/tests/loop_test_Newman_Kong.R
PAFit/tests/test_true_f.R
PAFit/tests/loop_joint_estimate.R
PAFit/tests/test_joint_estimate.R
PAFit/tests/test_GetStatistics_undirected.R
PAFit/src
PAFit/src/Makevars
PAFit/src/Cpp_code.cpp
PAFit/src/Makevars.win
PAFit/src/init.c
PAFit/src/RcppExports.cpp
PAFit/NAMESPACE
PAFit/data
PAFit/data/ComplexNetCoauthor.rda
PAFit/R
PAFit/R/perform_CV_core.R PAFit/R/Generate_fitonly.R
PAFit/R/plot.pafit_result.r
PAFit/R/OnlyF_Estimate.R PAFit/R/CreateDataCV.R
PAFit/R/summary.pafit_data.r
PAFit/R/summary.pa_result.R PAFit/R/plot.pa_result.R PAFit/R/performCV_old.R PAFit/R/print.CV_Result.R
PAFit/R/print.pafit_result.r
PAFit/R/print.pa_result.R PAFit/R/PAFit.R PAFit/R/Generate_ER.R PAFit/R/GenerateNet.R PAFit/R/RcppExports.R PAFit/R/summary.CV_Result.R PAFit/R/OnlyF_CV.R PAFit/R/GetStatistics.R PAFit/R/Jeong.R PAFit/R/CreateDataCV_new.R PAFit/R/OnlyA_CV.R PAFit/R/CreateDataCV_onlyA.R PAFit/R/summary.cv_data.R PAFit/R/OnlyA_Estimate.R
PAFit/R/print.pafit_data.r
PAFit/R/print.cv_data.R PAFit/R/JointEstimate.R PAFit/R/Newman.R
PAFit/R/summary.pafit_result.r
PAFit/R/Generate_BA.R PAFit/R/Generate_BB.R
PAFit/vignettes
PAFit/vignettes/Tutorial.pdf.asis
PAFit/MD5
PAFit/build
PAFit/build/vignette.rds
PAFit/DESCRIPTION
PAFit/man
PAFit/man/OnlyA_Estimate.rd
PAFit/man/plot.PAFit_result.Rd PAFit/man/GetStatistics.Rd
PAFit/man/plot.PA_result.rd
PAFit/man/Jeong.rd
PAFit/man/Newman.rd
PAFit/man/Generate_BA.rd
PAFit/man/Generate_fitonly.rd
PAFit/man/GenerateNet.Rd
PAFit/man/Generate_ER.rd
PAFit/man/OnlyF_Estimate.rd
PAFit/man/ComplexNetCoauthor.rd
PAFit/man/Generate_BB.rd
PAFit/man/PAFit-package.Rd
PAFit/man/JointEstimate.rd

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