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

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Salah, Khardani | Baba, Thiam

Edité par HAL CCSD ; Taylor & Francis

International audience. 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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