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Thursday 19 Jan 2017Statistical Science Seminar: Dependent Generalised Dirichlet Process Priors

Maria De lorio - University College London

H101 15:00-16:30

We propose a novel Bayesian nonparametric process prior for modelling a collections of

random discrete distributions. This process is defined by combining a Generalised Dirich-

let Process with a suitable Beta regression framework that introduces dependence among the

discrete random distributions. This strategy allows for covariate dependent clustering of the

observations. Some advantages of the proposed approach include wide applicability, ease of

interpretation and efficient MCMC algorithms. The methodology is illustrated through two

real data applications involving acute lymphoblastic leukaemia and London primary schools

quality evaluations.

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