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StochBlock  

Stochastic Blockmodeling of One-Mode and Linked Networks
View on CRAN: Click here


Download and install StochBlock package within the R console
Install from CRAN:
install.packages("StochBlock")

Install from Github:
library("remotes")
install_github("cran/StochBlock")

Install by package version:
library("remotes")
install_version("StochBlock", "0.1.2")



Attach the package and use:
library("StochBlock")
Maintained by
Aleš Žiberna
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-24
Latest Update: 2023-01-24
Description:
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).
How to cite:
Aleš Žiberna (2023). StochBlock: Stochastic Blockmodeling of One-Mode and Linked Networks. R package version 0.1.2, https://cran.r-project.org/web/packages/StochBlock. Accessed 22 Dec. 2024.
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Complete documentation for StochBlock
Functions, R codes and Examples using the StochBlock R package
Some associated functions: ICLStochBlock . StochBlock-package . findActiveParam . llStochBlock . stochBlock . stochBlockKMint . stochBlockORP . weightsMlLoglik . 
Some associated R codes: ICL.R . RcppExports.R . StochBlock-package.R . helperFunctions.R . onAttach.R . stochBlockKMint.R .  Full StochBlock package functions and examples
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