Properties of uniform consistency of the kernel estimators of density and regression functions under dependence assumptions

Abstract

The paper contains exponential inequalities for dependent random variables. As a measure of dependence we use φand ρ-mixing coefficients, the last one being based on the maximal coefficient of correlation. These results allow us to study the problem of uniform strong convergence for the kernel estimators of a density and for a kernel predictor for stochastic processes. Our uniform consistency theorems extend some known results