We propose a fast data-driven procedure for decomposing seasonal time series using the Berlin Method, the software used by the German Federal Statistical Office in this context. Formula of the asymptotic optimal bandwidth h_A is obtained. Meth- ods for estimating the unknowns in h_A are...

This paper summarizes recent developments in non- and semiparametric regres- sion with stationary fractional time series errors, where the error process may be short-range, long-range dependent or antipersistent. The trend function in this model is estimated nonparametrically, while the...

This paper summarizes recent developments in non- and semiparametric regression with stationary fractional time series errors, where the error process may be short-range, long-range dependent or antipersistent. The trend function in this model is estimated nonparametrically, while the dependence...

This paper proposes a local linear estimator for diurnal patterns of transaction durations under a special nonparametric regression model, whose asymptotics are different to any known results. An iterative plug-in algorithm is developed for selecting the bandwidth. The ACD model is then applied...

Realized kernels introduced by Barndorff-Nielsen et al. (2008) are consistent estimators of the daily integrated volatility in the presence of microstructure noise. A crucial problem by applying realized kernels is the selection of the bandwidth. This paper proposes an iterative plug-in...

This paper summarizes recent developments in non- and semiparametric regres- sion with stationary fractional time series errors, where the error process may be short-range, long-range dependent or antipersistent. The trend function in this model is estimated nonparametrically, while the...

In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss. These measures result in a rule of thumb, a...