A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data

Elias Ould-Saïd; Djabrane Yahia; Abdelhakim Necir

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arXiv · 0810.1156

A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data

Elias Ould-Saïd·Djabrane Yahia·Abdelhakim Necir

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Abstract

In this paper we study some asymptotic properties of the kernel conditional quantile estimator with randomly left-truncated data which exhibit some kind of dependence. We extend the result obtained by Lemdani, Ould-Saïd and Poulin [16] in the iid case. The uniform strong convergence rate of the estimator under strong mixing hypothesis is obtained.

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Elias Ould-Saïd, Djabrane Yahia, Abdelhakim Necir. 2008-10-07. A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data. https://arxiv.org/abs/0810.1156

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