European clinical guidelines for Tourette syndrome and other tic disorders. Part II: pharmacological treatment

To develop a European guideline on pharmacologic treatment of Tourette syndrome (TS) the available literature was thoroughly screened and extensively discussed by a working group of the European Society for the Study of Tourette syndrome (ESSTS). Although there are many more studies on pharmacotherapy of TS than on behavioral treatment options, only a limited number of studies meets rigorous quality criteria. Therefore, we have devised a two-stage approach. First, we present the highest level of evidence by reporting the findings of existing Cochrane reviews in this field. Subsequently, we provide the first comprehensive overview of all reports on pharmacological treatment options for TS through a MEDLINE, PubMed, and EMBASE search for all studies that document the effect of pharmacological treatment of TS and other tic disorders between 1970 and November 2010. We present a summary of the current consensus on pharmacological treatment options for TS in Europe to guide the clinician in daily practice. This summary is, however, rather a status quo of a clinically helpful but merely low evidence guideline, mainly driven by expert experience and opinion, since rigorous experimental studies are scarce

Nonparametric regression under dependent errors with infinite variance

We consider local least absolute deviation (LLAD) estimation for trend functions of time series with heavy tails which are characterised via a symmetric stable law distribution. The setting includes both causal stable ARMA model and fractional stable ARIMA model as special cases. The asymptotic limit of the estimator is established under the assumption that the process has either short or long memory autocorrelation. For a short memory process, the estimator admits the same convergence rate as if the process has the finite variance. The optimal rate of convergence n−2/5 is obtainable by using appropriate bandwidths. This is distinctly different from local least squares estimation, of which the convergence is slowed down due to the existence of heavy tails. On the other hand, the rate of convergence of the LLAD estimator for a long memory process is always slower than n−2/5 and the limit is no longer normal