A strong uniform convergence rate of a kernel conditional quantile   estimator under random left-truncation and dependent data
  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. 
Elias Ould-Sa\"id, Djabrane Yahia, Abdelhakim Necir