The paper describes a case study in combining different methods for acquiring medical knowledge. Given a huge amount of noisy, high dimensional numerical time series data describing patients in intensive care, the support vector machine is used to learn when and how to change the dose of which...

This paper generalizes Kushner's (1997) method for finding optimal repeated measurements designs to optimal designs under an interference model. The model we assume is for a onedimensional layout without guard plots and with different left and right neighbour effects. The resulting optimal...

We show that there is strong evidence of long-range dependence in the volatilities of several German stock returns. This will be done by estimating the memory parameter of the absolute returns with classical log-periodogram regression as well as by employing the tapered periodogram. Both...

The structural analysis of proteins is fundamental to the analysis of protein functions. In this context, sequence-structure alignment methods are important among the different empirical methods. In order to assess the quality of sequence-structure alignments, a statistical method using a...

In this article we highlight the main differences of available methods for the analysis of regression functions that are probably additive separable. We first discuss definition and interpretation of the most common estimators in practice. This is done by explaining the different ideas of...

Training a support vector machine SVM leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large...