A SEMIPARAMETRIC BAYESIAN APPROACH TO NETWORK MODELLING USING DIRICHLET PROCESS PRIOR DISTRIBUTIONS

DOI10.1111/J.1467-842X.2010.00583.XzbMath1373.62221OpenAlexW2005265490MaRDI QIDQ5357579

No author found.

Publication date: 11 September 2017

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-842x.2010.00583.x

zbMATH Keywords

clusteringDirichlet processnetwork modelssocial relations\textsc{WinBUGS} softwareBayesian semiparametric modelling

Mathematics Subject Classification ID

Social networks; opinion dynamics (91D30) Applications of statistics to social sciences (62P25) Bayesian inference (62F15) Nonparametric inference (62G99)

Related Items (3)

Dynamic degree-corrected blockmodels for social networks: A nonparametric approach ⋮ Stylometric analyses using Dirichlet process mixture models ⋮ A flexible approach for multivariate mixed-effects models with non-ignorable missing values

Uses Software

• WinBUGS

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