STRONG CONSISTENCY RATE OF THE CONDITIONAL QUANTILE ESTIMATOR WITH DATA MISSING AT RANDOM

Abstract

In the case of response missing at random conditioned by a functional explanatory variable, this research investigates non parametric estimate of the conditional quantile using the kernel approach. Under an α-mixing assumption and properties of the small ball, we establish the uniform almost complete convergence (with rate) of the proposed estimator.