Open Access
April 2003 Estimating multiplicative and additive hazard functions by kernel methods
Oliver B. Linton, Jens Perch Nielsen, Sara Van de Geer
Ann. Statist. 31(2): 464-492 (April 2003). DOI: 10.1214/aos/1051027877


We propose new procedures for estimating the component functions in both additive and multiplicative nonparametric marker-dependent hazard models. We work with a full counting process framework that allows for left truncation and right censoring and time-varying covariates. Our procedures are based on kernel hazard estimation as developed by Nielsen and Linton and on the idea of marginal integration. We provide a central limit theorem for the marginal integration estimator. We then define estimators based on finite-step backfitting in both additive and multiplicative cases and prove that these estimators are asymptotically normal and have smaller variance than the marginal integration method.


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Oliver B. Linton. Jens Perch Nielsen. Sara Van de Geer. "Estimating multiplicative and additive hazard functions by kernel methods." Ann. Statist. 31 (2) 464 - 492, April 2003.


Published: April 2003
First available in Project Euclid: 22 April 2003

zbMATH: 1040.62089
MathSciNet: MR1983538
Digital Object Identifier: 10.1214/aos/1051027877

Primary: 62G05 , 62M09

Keywords: Additive model , Censoring , ‎kernel‎ , proportional hazards , Survival analysis

Rights: Copyright © 2003 Institute of Mathematical Statistics

Vol.31 • No. 2 • April 2003
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