A semiparametric Bayesian approach to network modelling using Dirichlet process prior distributions

Authors

Pulak Ghosh
Paramjit Gill
Saman Muthukumarana
Tim Swartz

Document Type

Article

Publication Title

Australian and New Zealand Journal of Statistics

Abstract

This paper considers the use of Dirichlet process prior distributions in the statistical analysis of network data. Dirichlet process prior distributions have the advantages of avoiding the parametric specifications for distributions, which are rarely known, and of facilitating a clustering effect, which is often applicable to network nodes. The approach is highlighted for two network models and is conveniently implemented using WinBUGS software.

DOI Link

https://doi.org/10.1111/j.1467-842X.2010.00583.x

Publication Date

1-4-2010

Publisher

Wiley||Australian Statistical Publishing Association

Volume

Vol.52

Issue

Iss.3

Recommended Citation

Ghosh, Pulak; Gill, Paramjit; Muthukumarana, Saman; and Swartz, Tim, "A semiparametric Bayesian approach to network modelling using Dirichlet process prior distributions" (2010). Faculty Publications. 816.
https://research.iimb.ac.in/fac_pubs/816