The basic ideas of Desirability functions and indices are introduced and compared to other methods of multivariate optimisation. It is shown that gradient based techniques are not in general appropriate to perform the numerical optimisation for Desirability indices. The problems are shown for...

Clinical information systems can record numerous variables describing the patient’s state at high sampling frequencies. Intelligent alarm systems and suitable bedside decision support are needed to cope with this flood of information. A basic task here is the fast and correct detection of...

This paper introduces ideas and methods for testing for structural change in linear regression models and presents how these have been realized in an R package called strucchange. It features tests from the generalized uctuation test framework as well as from the F test (Chow test) framework....

The one-way analysis of variance is concerned with comparing the locations of several one-dimensional samples. This paper gives a simple unified semi-graphical and semi-analytical approach to the problem based on approximation intervals for the locations of the samples. The intervals are...

Methods of dimension reduction are very helpful and almost a necessity if we want to analyze high-dimensional time series since otherwise modelling affords many parameters because of interactions at various time-lags. We use a dynamic version of Sliced Inverse Regression (SIR; Li (1991)), which...

In this paper, hidden Markov models (HMMs) are discussed in the context of molecular biological sequence analysis. The statistics relevant in the HMM approach are described in detail. An HMM based method is used to analyze two proteins that contain short protein repeats (SPRs). As a benchmark, a...