CRAN/E | SBMSplitMerge

SBMSplitMerge

Inference for a Generalised SBM with a Split Merge Sampler

Installation

About

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) .

Key Metrics

Version 1.1.1
R ≥ 3.1.0
Published 2020-06-04 1474 days ago
Needs compilation? no
License MIT
License File
CRAN checks SBMSplitMerge results
Language en-GB

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Maintainer

Maintainer

Matthew Ludkin

Authors

Matthew Ludkin

aut / cre / cph

Material

README
NEWS
Reference manual
Package source

Vignettes

Weibull-edges

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.1.0

Imports

ggplot2
scales
reshape2

Suggests

knitr
rmarkdown