Empirical process theory provides a rich toolbox for studying the properties of empirical risk minimizers, such as least squares and maximum likelihood estimators, support vector machines, etc.

In this course we study the basics of theoretical statistics. The course includes methods for designing estimators, confidenceintervals and tests, and various ways to evaluate the accuracy ofestimators, confidence intervals and tests. We consider optimality criteria such as admissibility and minimaxity, as well asBayesian criteria. We will also present the asymptotic point of view.

In this course we study the basics of theoretical statistics. The course includes methods for designing estimators, confidenceintervals and tests, and various ways to evaluate the accuracy ofestimators, confidence intervals and tests. We consider optimality criteria such as admissibility and minimaxity, as well asBayesian criteria. We will also present the asymptotic point of view.

- Diskrete Wahrscheinlichkeitsräume- Stetige Modelle- Grenzwertsätze- Einführung in die Statistik

Regression studies the dependence of a random response variable on other variables. We consider the theory and application of linear regression with one or more covariates. Various extensions such as nonlinear models, generalized linear models, nonparametric models, robust methods, and model selection are discussed.