README.md

In mlsbm: Efficient Estimation of Bayesian SBMs & MLSBMs

mlsbm

The mlsbm package fits single level stochastic block models (SBMs) and multilevel stochastic block models (MLSBMs) using efficient Gibbs sampling with Rcpp. It can also be used to efficiently sample from SBMs and MLSBMs.

Installation

The mlsbm package can be installed directly from this repository using devtools.

devtools::install_github("carter-allen/mlsbm")

Usage

# load mlsbm package
library(mlsbm)

# load included 3-layer network data
data(AL)

# fit a multilevel SBM with 3 clusters
fit <- fit_mlsbm(AL,3)

# examine the inferred clustering
table(fit$z)

mlsbm documentation built on Feb. 7, 2021, 5:05 p.m.