mcPAFit: Estimating Preferential Attachment from a Single Network Snapshot by Markov Chain Monte Carlo

A Markov chain Monte Carlo method is provided to estimate the preferential attachment function from a single network snapshot. Conventional methods require the complete information about the appearance order of all nodes and edges in the network. This package incorporates the appearance order into the state space and estimates it together with the preferential attachment function. Auxiliary variables are introduced to facilitate fast Gibbs sampling.

Author
Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Date of publication
2016-05-25 15:52:19
Maintainer
Thong Pham <thongpham@thongpham.net>
License
GPL-3
Version
0.1.3

View on CRAN

Man pages

create_sim_data
Generating simulated networks
mcPAFit
estimates the Preferential Attachment function in a temporal...
mcPAFit-package
Estimating Preferential Attachment from a Single Network...

Files in this package

mcPAFit
mcPAFit/src
mcPAFit/src/Makevars
mcPAFit/src/Cpp_code.cpp
mcPAFit/src/Makevars.win
mcPAFit/src/RcppExports.cpp
mcPAFit/NAMESPACE
mcPAFit/R
mcPAFit/R/RcppExports.R
mcPAFit/R/mcPAFit.R
mcPAFit/R/create_sim_data.R
mcPAFit/MD5
mcPAFit/DESCRIPTION
mcPAFit/man
mcPAFit/man/mcPAFit.Rd
mcPAFit/man/mcPAFit-package.Rd
mcPAFit/man/create_sim_data.Rd