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.
P. J. Brockwell and R. A. Davis. Introduction to time series analysis and forecasting. Springer, New York, 2. edition, 2002.
M. Deistler und W. Scherrer. Modelle der Zeitreihenanalyse. Birkhäuser, 2018.
