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 |
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 |
Reference manual: | StochBlock.pdf |
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-devel (arm64): StochBlock_0.1.2.tgz, r-release (arm64): StochBlock_0.1.2.tgz, r-oldrel (arm64): StochBlock_0.1.2.tgz, r-devel (x86_64): StochBlock_0.1.2.tgz, r-release (x86_64): StochBlock_0.1.2.tgz, r-oldrel (x86_64): StochBlock_0.1.2.tgz |
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