Asymptotic Normality of a Nonparametric Conditional Quantile Estimator for Random Fields

摘要

Given a stationary multidimensional spatial process (Z_i = (X_i, Y_i) ∈ R~d × R, i ∈ Z~N), we investigate a kernel estimate of the spatial conditional quantile function of the response variable Y_i given the explicative variable X_i. Asymptotic normality of the kernel estimate is obtained when the sample considered is an α-mixing sequence.