StochBlock: Stochastic Blockmodeling of One-Mode and Linked Networks

Stochastic blockmodeling of one-mode and linked networks as implemented in Škulj and Žiberna (2022) <doi:10.1016/j.socnet.2022.02.001>. The optimization is done via CEM (Classification Expectation Maximization) algorithm that can be initialized by random partitions or the results of k-means algorithm. The development of this package is financially supported by the Slovenian Research Agency (<https://www.arrs.si/>) within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different approaches to blockmodeling dynamic networks by simulations with application to Slovenian co-authorship networks).

Version:	0.1.2
Imports:	blockmodeling, doParallel, doRNG, foreach, Rcpp (≥ 1.0.0)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2023-01-24
DOI:	10.32614/CRAN.package.StochBlock
Author:	Aleš Žiberna [aut, cre], Fabio Ashtar Telarico [ctb]
Maintainer:	Aleš Žiberna <ales.ziberna at fdv.uni-lj.si>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
SystemRequirements:	C++11
Citation:	StochBlock citation info
CRAN checks:	StochBlock results

Documentation:

Reference manual:

StochBlock.pdf

Downloads:

Package source:	StochBlock_0.1.2.tar.gz
Windows binaries:	r-devel: StochBlock_0.1.2.zip, r-release: StochBlock_0.1.2.zip, r-oldrel: StochBlock_0.1.2.zip
macOS binaries:	r-release (arm64): StochBlock_0.1.2.tgz, r-oldrel (arm64): StochBlock_0.1.2.tgz, r-release (x86_64): StochBlock_0.1.2.tgz, r-oldrel (x86_64): StochBlock_0.1.2.tgz

Linking:

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