A note on the finite-dimensional Dirichlet prior

Xia Yemao and Gou Jianwei

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 19, 9388-9396

Abstract: As an approximation to the Dirichlet process which involves the infinite-dimensional distribution, finite-dimensional Dirichlet prior is a widely appreciated method to model the underlying distribution in non parametric Bayesian analysis. In this short note, we present some key characteristics of finite-dimensional Dirichlet process and exploit some important sampling properties which are very useful in Bayesian non parametric/semiparametric analysis.

Date: 2017
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DOI: 10.1080/03610926.2016.1208239

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