After successful completion of the course, students are able to formulate and prove the basic theorems of stationary processes and their spectral representation as well as making forecasts and to perform statistical estimation and testing in this context.

Stationary processes, basics, autocovariance function, spectral representation, spectrum, linear filters, transferfunction, AR/ARMA processes, forecasting, estimation.

Lectures with slides.

Documents, exercises, etc. are provided in the associated TUWEL course. Therefore, registration in the TUWEL course is absolutely necessary. (The non-binding registration is done by "self-enrollment").

Oral exam by appointment.

P. J. Brockwell and R. A. Davis. Introduction to time series analysis and forecasting. Springer, New York, 2. edition, 2002.

M. Deistler and W. Scherrer. Time Series Models. Springer, 2022.

Foundations in linear algebra, probability theory and statistics are recommended.