Work

mlsbm: Efficient Estimation of Bayesian SBMs & MLSBMs

Year: 2021

Type: dataset

Abstract: Fit Bayesian stochastic block models (SBMs) and multi-level stochastic block models (MLSBMs) using efficient Gibbs sampling implemented in 'Rcpp'. The models assume symmetric, non-reflexive graphs (no self-loops) with unweighted, binary edges. Data are input as a symmetric binary adjacency matrix (SBMs), or list of such matrices (MLSBMs).

DOI: 10.32614/cran.package.mlsbm

Authors: Carter Allen, Dongjun Chung

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

OpenAlex ID: W4399523354

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Cited by: 2

Related to: 10