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Linear and quadratic functionals of random hazard rates: an asymptotic analysis (2006)

Abstract
A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results for linear and quadratic functionals of such random hazard rates. In particular, we prove central limit theorems for the cumulative hazard function and for the path-second moment and path-variance of the hazard rate. Our techniques are based on recently established criteria for the weak convergence of single and double stochastic integrals with respect to Poisson random measures. We illustrate our results by considering specific models involving kernels and random measures commonly exploited in practice.

Publication details
Download http://hal.archives-ouvertes.fr/hal-00115565/en/
Publisher HAL - CCSD
Repository CCSd/HAL : e-articles server (based on gBUS) (France)
Keywords Mathematics/Probability, Mathematics/Statistics, Statistics/Theory, Asymptotics, Bayesian Nonparametrics, Central limit theorem, Path-variance, Random hazard rate, Survival analysis, Completely random measure, Multiple Wiener-Itô integral
Language English
Relation http://hal.archives-ouvertes.fr/docs/00/11/55/66/PDF/hazards_arxiv.pdf

Cited publications (10)
Generalized gamma measures and shot-noise Cox processes (1998)
Some new results for Dirichlet priors (2000)
A Bayes method for a monotone hazard rate via S-paths (2006)
Bayesian Variable Selection for Proportional Hazards Models (1999)
Gibbs Sampling Methods for Stick-Breaking Priors (2000)
Poisson calculus for spatial neutral to the right processes (2006)
Nonparametric Bayesian estimators for counting processes (1999)
Bayesian analysis of proportional hazard models (2003)
Completely random measures. (1967)
Anticipative calculus for the Poisson process based on the Fock space (1990)