The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

SBMSplitMerge: Inference for a Generalised SBM with a Split Merge Sampler

Inference in a Bayesian framework for a generalised stochastic block model. The generalised stochastic block model (SBM) can capture group structure in network data without requiring conjugate priors on the edge-states. Two sampling methods are provided to perform inference on edge parameters and block structure: a split-merge Markov chain Monte Carlo algorithm and a Dirichlet process sampler. Green, Richardson (2001) <doi:10.1111/1467-9469.00242>; Neal (2000) <doi:10.1080/10618600.2000.10474879>; Ludkin (2019) <doi:10.48550/arXiv.1909.09421>.

Version: 1.1.1
Depends: R (≥ 3.1.0)
Imports: ggplot2, scales, reshape2
Suggests: knitr, rmarkdown
Published: 2020-06-04
DOI: 10.32614/CRAN.package.SBMSplitMerge
Author: Matthew Ludkin [aut, cre, cph]
Maintainer: Matthew Ludkin <m.ludkin1 at lancaster.ac.uk>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-GB
Materials: README NEWS
CRAN checks: SBMSplitMerge results

Documentation:

Reference manual: SBMSplitMerge.pdf
Vignettes: Weibull-edges

Downloads:

Package source: SBMSplitMerge_1.1.1.tar.gz
Windows binaries: r-devel: SBMSplitMerge_1.1.1.zip, r-release: SBMSplitMerge_1.1.1.zip, r-oldrel: SBMSplitMerge_1.1.1.zip
macOS binaries: r-release (arm64): SBMSplitMerge_1.1.1.tgz, r-oldrel (arm64): SBMSplitMerge_1.1.1.tgz, r-release (x86_64): SBMSplitMerge_1.1.1.tgz, r-oldrel (x86_64): SBMSplitMerge_1.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SBMSplitMerge to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.