On the rate of convergence to the normal law of LSE in regression with long range dependence

Abstract

In this paper we study the rate of convergence to the normal approximation of the least squares estimators in a regression model with long range dependent errors. The method of investigation used is based on the asymptotic analysis of orthogonal expansions of non linear functionals of stationary Gaussian processes and on Kolmogorov's distance.