A strong linear representation for the maximum conditional hazard rate estimator in survival analysis

Quintela-del-Río (2006) considered the estimation of the maximum hazard under dependence conditions and established strong convergence with rate and asymptotic normality of the estimate. The aim of this paper is to generalize this work to the case of right censored data with covariate. Via a consist...

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Bibliographic Details
Published in:Journal of multivariate analysis 2014-07, Vol.128, p.10-18
Main Author: Gneyou, Kossi Essona
Format: Article
Language:English
Subjects:
Asymptotic methods
Conditional hazard rate
Estimating techniques
Kernel
Mathematical functions
Maximum conditional hazard rate
Nonparametric estimation
Parameter estimation
Right censoring
Studies
Survival analysis
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Summary:Quintela-del-Río (2006) considered the estimation of the maximum hazard under dependence conditions and established strong convergence with rate and asymptotic normality of the estimate. The aim of this paper is to generalize this work to the case of right censored data with covariate. Via a consistently Nadaraya–Watson weighted type estimator of the conditional hazard function, we get a non-parametric estimator of its maximum value. We establish strong representation and strong uniform consistency results for our estimators.
ISSN:0047-259X
1095-7243
DOI:10.1016/j.jmva.2014.02.013