Nonparametric regression with heteroscedastic long memory errors

This paper discusses the estimation of regression and variance functions in nonparametric heteroscedastic regression models with long memory moving average errors and uniform nonrandom design on the unit interval. The consistency and the finite dimensional weak convergence of these estimators are established. For the regression function estimators, the asymptotic normality is established for all values of the long memory parameter 12