Strong consistency result of a non parametric conditional mode estimator under random censorship for functional regressors

Abstract : Let (T, C, X) be a vector of random variables (rvs) where T, C, and X are the interest variable, a right censoring rv, and a covariate, respectively. In this paper, we study the kernel conditional mode estimation when the covariate takes values in an infinite dimensional space and is α-mixing. Under some regularity conditions, the almost complete convergence of the estimate with rates is established.
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Communications in Statistics - Theory and Methods, 2016, 45 (7), pp.1863--1875. 〈10.1080/03610926.2013.867997〉
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Contributeur : Romain Boisselet <>
Soumis le : lundi 22 mai 2017 - 15:25:37
Dernière modification le : mardi 3 juillet 2018 - 11:23:50

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Khardani Salah, Thiam Baba. Strong consistency result of a non parametric conditional mode estimator under random censorship for functional regressors. Communications in Statistics - Theory and Methods, 2016, 45 (7), pp.1863--1875. 〈10.1080/03610926.2013.867997〉. 〈hal-01526023〉

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