For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data generating process and in a second step statistical inference is performed in the identified model. An intuitively appealing approach to the design of...

In this paper we describe a computer intensive method to find the ridge parameter in a prediction oriented linear model. With the help of a factorial experimental design the method is tested and compared to a classical one.

In nonparametric curve estimation the decision about the type of smoothing parameter is critical for the practical performance. The nearest neighbor bandwidth as introduced by Gefeller and Dette 1992 for censored data in survival analysis is specified by one parameter, namely the number of...

Microarrays enable to measure the expression levels of tens of thousands of genes simultaneously. One important statistical question in such experiments is which of the several thousand genes are differentially expressed. Answering this question requires methods that can deal with multiple...

We consider a misconception common among students of statistics involving "adjusted" and "unadjusted" sums-of-squares. While the presence of misconception has been noted before (e.g. Hamilton (1986)), we argue that it may be related to the language we use in describing the meaning of...

For the common binary response model we propose a direct method for the nonparametric estimation of the effective dose level ED? (0 ? 1). The estimator is obtained by the composition of a nonparametric estimate of the quantile response curve and a classical density estimate. The new method...

In this note we examine the relevance of Sheppards correction for variances and (both the original and a valid weak form of) the so-called quantization noise model to understanding the effects of integer-rounding on continuous random variables. We further consider whether there is any real...

The goals of this paper are twofold: we describe common features in data sets from motor vehicle insurance companies and we investigate a general strategy which exploits the knowledge of such features. The results of the strategy are a basis to develop insurance tariffs. The strategy is applied...

We consider the design problem for the estimation of several scalar measures suggested in the epidemiological literature for comparing the success rate in two samples. The designs considered so far in the literature are local in the sense that they depend on the unknown probabilities of success...