Bergm: Bayesian Exponential Random Graphs inR | Zendy

Alberto Caimo | Zendy; Nial Friel | Zendy

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Bergm: Bayesian Exponential Random Graphs inR

Author(s) -

Alberto Caimo,

Nial Friel

Publication year - 2014

Publication title -

journal of statistical software

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.636

H-Index - 145

ISSN - 1548-7660

DOI - 10.18637/jss.v061.i02

Subject(s) - exponential random graph models , computer science , bayesian probability , random graph , exponential function , r package , model selection , graph , exponential family , software , algorithm , theoretical computer science , data mining , mathematics , artificial intelligence , machine learning , programming language , mathematical analysis

In this paper we describe the main featuress of the Bergm package for the open-source R software which provides a comprehensive framework for Bayesian analysis for exponential random graph models: tools for parameter estimation, model selection and goodness-of-fit diagnostics. We illustrate the capabilities of this package describing the algorithms through a tutorial analysis of two well-known network datasets.

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