A Semiparametric Bayesian Approach to Network Modelling using Dirichlet Process Priors
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چکیده
This paper considers the use of Dirichlet process priors in the statistical analysis of network data. Dirichlet process priors have the advantage of avoiding the parametric specification for distributions which are rarely known and for facilitating a clustering effect which is often applicable to network nodes. The approach is highlighted on two network models and is conveniently implemented using WinBUGS software.
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تاریخ انتشار 2009