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