In this paper we consider the asymptotic distribution of S -estimators in the nonlinear regression model with long-memory error terms. S - estimators are robust estimates with a high breakdown point and good asymptotic properties in the i.i.d case. They are constructed for linear regression. In...

We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind...

We discuss the increasing literature on misspecifying structural breaks or more general trends as long range dependence. We consider tests on structural breaks in the long-memory regression model as well as the behaviour of estimators of the memory parameter when structural breaks or trends are...

Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if...