Asymptotic normality of a nonparametric conditional quantile estimator for random fields
Summary: Given a stationary multidimensional spatial process \(\{Z_i = (X_i, Y_i) \in \mathbb R^d \times \mathbb R,\;i \in \mathbb Z^N\}\), 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 \(\alpha\)-mixing sequence.
scientific article; zbMATH DE number 6014711
scientific article