On the rate of asymptotic normality of integral weighted kernel estimator in a non parametric regression model for φ-mixing random variables

Abstract

. In this article, we study the convergence rate of asymptotic normality for the estimator in a non parametric regression model under φ-mixing random variables by using the blockwise technique. With different choices of the parameters, the rates are shown as O ( n − 1 / 9 ) and O ( n − 1 / 6 ) . We also carry out some simulation studies and a real data analysis to support the theoretical results established here.