Conditional risk estimate for functional data under strong mixing conditions

Abstract

We consider the problem of nonparametric estimation of the conditional hazard function for functional mixing data. More precisely, given a strictly stationary random variables Z i = (X i , Y i ) i∈N , we investigate a kernel estimate of the conditional hazard function of univariate response variable Y i given the functional variable X i . The principal aim of this paper is to give the mean squared convergence rate and to prove the asymptotic normality of the proposed estimator.