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Strong uniform consistency rates of conditional hazard estimation in the single functional index model for dependant functional data under random censorship

Amina A. Bouchentouf, Aicha Hamza, Abbes Rabhi


This paper presents a nonparametric estimation of the conditional hazard function, when the covariate is functional and when the sample is considered as an α-mixing sequence. We prove consistency properties (with rates) in various situations, including censored and uncensored variables; the pointwise almost complete convergence and the uniform almost complete convergence (with rates) of the kernel estimator of this model are established.


Censored data, conditional hazard function, functional variable, nonparametric estimation, single functional index process, strong mixing processes.

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