Einf(c)ơhrung -- Mehrdimensionale Zufallsvariablen und Verteilungen -- Grundlegende multivariate Sch(c)Þtz- und Testprobleme -- Regressionsanalyse -- Varianz- und Kovarianzanalyse -- Kategoriale und generalisierte lineare Regression -- Regressionsmodelle zur Analyse von Verweildauern --...

The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as linearity of the predictor or the...

Overdispersion in count data regression is often caused by neglection or inappropriate modelling of individual heterogeneity, temporal or spatial correlation, and nonlinear covariate effects. In this paper, we develop and study semiparametric count data models which can deal with these issues by...

Spline smoothing in non- or semiparametric regression models is usually based on the roughness penalty approach. For regression with normal errors, the spline smoother also has a Bayesian justification: Placing a smoothness prior over the regression function, it is the mean of the posterior...

There are two popular smoothing parameter selection methods for spline smoothing. First, criteria that approximate the average mean squared error of the estimator (e.g. generalized cross validation) are widely used. Alternatively, the maximum likelihood paradigm can be employed under the...