1. Cowpertwait, Metcalfe: Introductory Time Series with R, Springer
2. Brockwell, Davis: Introduction to Time Series and Forecasting, Springer

Course starts with the lab on 11.04.

Please also enroll in the learnweb course - it opens 11.04; no password required.

Time Series Analysis from the viewpoint of Mathematical Stochastics. The following topics will be covered:

• Decomposition: Identification of trends and seasonal components
• Models for discrete time series: Autoregressive Models, Moving Average Models and ARMA models, parameter estimation for these models
• Models for heteroskedasticity: ARCH and GARCH models and parameter estimation
• Aspects of extreme value theory for time series
• Models for continuous time series: Brownian motion and related stochastic processes - if time permits.