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

Gagui Abdelmalek () and Chouaf Abdelhak ()
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Gagui Abdelmalek: , Djillali Liabes University, Algeria .
Chouaf Abdelhak: , Djillali Liabes University, Algeria .

Statistics in Transition New Series, 2022, vol. 23, issue 2, 89-105

Abstract: 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.

Keywords: single functional index; conditional hazard function; nonparametric estimation; α-mixing dependency; asymptotic normality; functional data (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:23:y:2022:i:2:p:89-105:n:6

DOI: 10.2478/stattrans-2022-0018

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