Time Series Analysis
Instructor | Achim Zeileis |
Timeline | Course Catalog |
Learning resources | OLAT Learning Management System (also via guest access) |
Primary reference | Cryer & Chan (2008). Time Series Analysis - With Applications in R, 2nd ed. Springer-Verlag. R package, Springer homepage |
Secondary reference | Kleiber & Zeileis (2008). Applied Econometrics with R. Springer-Verlag. R package, Chapter 1 & 2, Springer homepage, Google books |
Contents
- Introduction
- Smoothing and decomposition methods
- Stochastic processes
- ARIMA models
- Stationarity, unit roots, and cointegration
- Time series regression and structural change
- GARCH models
- Multivariate time series models
Requirements
- Linear regression
- Ordinary/weighted/generalized least squares estimation
- Gauss-Markov theorem
- Inference (t and F tests) for linear hypotheses
- Robust standard errors
- Regression diagnostics
- Factors and interactions
- Model selection
Software
- R
The R system for statistical computing will be used throughout the lecture. All methods and their application will be illustrated using R. Exercises should be solved using R.
Installation under Windows: Base R. - Integrated development environment for R: RStudio
- Introduction to Programming with R