fit_mlsbm {mlsbm}

R/Rcpp function for fitting multilevel stochastic block model

Description

This function allows you to fit multilevel stochastic block models.

Usage

fit_mlsbm(
  A,
  K,
  a0 = 0.5,
  b10 = 0.5,
  b20 = 0.5,
  n_iter = 1000,
  burn = 100,
  verbose = TRUE
)

Arguments

A

An adjacency list of length L, the number of levels. Each level contains an n x n symmetric adjacency matrix.

K

The number of clusters specified a priori.

a0

Dirichlet prior parameter for cluster sizes for clusters 1,...,K.

b10

Beta distribution prior paramter for community connectivity.

b20

Beta distribution prior parameter for community connectivity.

n_iter

The number of total MCMC iterations to run.

burn

The number of burn-in MCMC iterations to discard. The number of saved iterations will be n_iter - burn.

verbose

Whether to print a progress bar to track MCMC progress. Defaults to true.

Value

A list of MCMC samples, including the MAP estimate of cluster indicators (z)

Examples

data(AL)
# increase n_iter in practice
fit <- fit_mlsbm(AL,3,n_iter = 100)