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

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

2008-10-07

arxiv.org/abs/0810.1156v1

Mathematics

Statistics Theory

Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics

Scientific paper

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-Sa\"id 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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