For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the assumed linear regression model. It is...

The incidence of a disease can be easily estimated from serial prevalence data. However, difficulties usually arise in the case of prevalence data measured only once. This paper presents and assesses various methods for estimating the incidence of a disease in the latter case. The focus is on...

Two different estimation techniques for the spectrum of a nonstationary time series are compared empirically. Both of them are assuming a time-dependent autoregressive (AR-) model for the data. The first estimation technique used is the Frequency State Dependent Model (FSDM-) technique (Schmitz...

A basic part in the risk assessment of potential carcinogens is the determination of toxicokinetic parameters. The partition of the xenobiotic in the body of experimental animals is a first step of the biochemical pathway of the formation of DNA adducts which might lead to the development of...

In this paper we derive asymptotic x 2 - tests for general linear hypotheses on variance components using repeated variance components models. In two examples, the two-way nested classification model and the two-way crossed classification model with interaction, we explicitly investigate the...

In this paper we use 4 different time series models to forecast sales in a goods management system. We use a variety of forecast combining techniques and measure the forecast quality by applying symmetric and asymmetric forecast quality measures. Simple, rank-, and criteria-based combining...