Package: StochBlock 0.1.2
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).
Authors:
StochBlock_0.1.2.tar.gz
StochBlock_0.1.2.zip(r-4.5)StochBlock_0.1.2.zip(r-4.4)StochBlock_0.1.2.zip(r-4.3)
StochBlock_0.1.2.tgz(r-4.4-x86_64)StochBlock_0.1.2.tgz(r-4.4-arm64)StochBlock_0.1.2.tgz(r-4.3-x86_64)StochBlock_0.1.2.tgz(r-4.3-arm64)
StochBlock_0.1.2.tar.gz(r-4.5-noble)StochBlock_0.1.2.tar.gz(r-4.4-noble)
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StochBlock.pdf |StochBlock.html✨
StochBlock/json (API)
# Install 'StochBlock' in R: |
install.packages('StochBlock', repos = c('https://aleszib.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:03dd47306b. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win-x86_64 | NOTE | Nov 01 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 01 2024 |
R-4.4-win-x86_64 | NOTE | Nov 01 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 01 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 01 2024 |
R-4.3-win-x86_64 | NOTE | Nov 01 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 01 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 01 2024 |
Exports:findActiveParamICLStochBlockllStochBlockstochBlockstochBlockKMintstochBlockORP
Dependencies:blockmodelingcodetoolsdigestdoParalleldoRNGforeachiteratorslatticeMatrixRcppRcppArmadillorngtools