Di Finetti Afternoon, two seminars on Non-Parametric Bayesian Analysis, 2-5pm

Dr Igor Pruenster (Torino, Italy)

Asymptotics for posterior hazards

A popular Bayesian nonpaametric approach to survival analysis consists in modelling hazard rates as kernel mixtures driven by a completely random measure.  A comprehensive analysis of the asymptotic behaviour of such models is provided.  Consistency of the posterior distribution is investigated and central limit theorems for both linear and quadratic functionals of the posterior hazaed rate are derived.  The general results are then specialized to various specific kernels and mixing measures, thus yielding consistency under minimal conditions and near central limit theorems for the distribution of functionals.

Joint work with P. De Blasi and G. Peccati