Inhalt
| Literatur |
- Cowpertwait, Metcalfe: Introductory Time Series with R, Springer
- Brockwell, Davis: Introduction to Time Series and Forecasting, Springer
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| Bemerkung |
Course starts with the lab on 14.04. Please also enroll in the learnweb course - it opens 14.04; no password required. |
| Lerninhalte |
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.
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