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Highly scalable maximum likelihood and conjugate Bayesian inference for ERGMs on graph sets with equivalent vertices

The exponential family random graph modeling (ERGM) framework provides a highly flexible approach for the statistical analysis of networks (i.e., graphs). As ERGMs with dyadic dependence involve normalizing factors that are extremely costly to compute, practical strategies for ERGMs inference genera...

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Detalles Bibliográficos
Autores principales: Yin, Fan, Butts, Carter T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417041/
https://www.ncbi.nlm.nih.gov/pubmed/36018834
http://dx.doi.org/10.1371/journal.pone.0273039