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August 2009 Asymptotics for posterior hazards
Pierpaolo De Blasi, Giovanni Peccati, Igor Prünster
Ann. Statist. 37(4): 1906-1945 (August 2009). DOI: 10.1214/08-AOS631


An important issue in survival analysis is the investigation and the modeling of hazard rates. Within a Bayesian nonparametric framework, a natural and popular approach is to model hazard rates as kernel mixtures with respect to a completely random measure. In this paper we provide a comprehensive analysis of the asymptotic behavior of such models. We investigate consistency of the posterior distribution and derive fixed sample size central limit theorems for both linear and quadratic functionals of the posterior hazard rate. The general results are then specialized to various specific kernels and mixing measures yielding consistency under minimal conditions and neat central limit theorems for the distribution of functionals.


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Pierpaolo De Blasi. Giovanni Peccati. Igor Prünster. "Asymptotics for posterior hazards." Ann. Statist. 37 (4) 1906 - 1945, August 2009.


Published: August 2009
First available in Project Euclid: 18 June 2009

zbMATH: 1168.62042
MathSciNet: MR2533475
Digital Object Identifier: 10.1214/08-AOS631

Primary: 60G57 , 62G20

Keywords: asymptotics , Bayesian consistency , Bayesian nonparametrics , central limit theorem , completely random measure , path-variance , random hazard rate , Survival analysis

Rights: Copyright © 2009 Institute of Mathematical Statistics


Vol.37 • No. 4 • August 2009
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