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On the nonparametric estimation of the conditional hazard estimator in a single functional index

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Gagui A., Chouaf A.

Statistics in Transition new series

2022

vol. 23

issue 2

89-105

This paper deals with the conditional hazard estimator of a real response where the variable is given a functional random variable (i.e it takes values in an infinite-dimensional space). Specifically, we focus on the functional index model. This approach offers a good compromise between nonparametric and parametric models. The principle aim is to prove the asymptotic normality of the proposed estimator under general conditions and in cases where the variables satisfy the strong mixing dependency. This was achieved by means of the kernel estimator method, based on a single-index structure. Finally, a simulation of our methodology shows that it is efficient for large sample sizes.

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1 Statistics in Transition new series

1 Chouaf A.

1 Gagui A.

1 2022

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On the nonparametric estimation of the conditional hazard estimator in a single functional index