event
Thursday 19 Jan 2017: Statistical 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.
