OLS is as efficient as GLS in the linear regression model with long-memory errors as the long-memory parameter approaches the boundary of the stationarity region, provided the model contains a constant term. This generalizes previous results of Samarov & Taqqu (Journal of Time Series Analysis 9...

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 behaviour of S - estimators in the linear regression model, when the error terms are long-memory Gaussian processes. It turns out that under mild regularity conditions S - estimators are still normally distributed with a similar variance - covariance structure as in the i.i.d...

We show how the rootogram - a graphical tool associated with the work of J. W. Tukey and originally used for assessing goodness of fit of univariate distributions - can help to diagnose and treat issues such as overdispersion and/or excess zeros in regression models for count data. Two empirical...

The rootogram is a graphical tool associated with the work of J. W. Tukey that was originally used for assessing goodness of t of univariate distributions. Here we show that rootograms are also useful for diagnosing and treating issues such as overdispersion and/or excess zeros in regression...