fit_sbm: R/Rcpp function for fitting single level stochastic block...

In mlsbm: Efficient Estimation of Bayesian SBMs & MLSBMs

Description

This function allows you to fit single level stochastic block models.

Usage

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

Arguments

A	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)
fit <- fit_sbm(AL[[1]],3)

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