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


  • 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


  • 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


  • 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