Time Series Analysis (Summer Semester 2016)
- Lecturer: Prof. Dr. Tilmann Gneiting
- Classes: Lecture (0161100), Problem class (0161110)
- Weekly hours: 2+1
Schedule | ||
---|---|---|
Lecture: | Tuesday 14:00-15:30 | SR 2.59 |
Problem class: | Wednesday 14:00-15:30 | SR 2.58 |
Friday 14:00-15:30 | SCC-PC-Pool L |
Lecturers | ||
---|---|---|
Lecturer | Prof. Dr. Tilmann Gneiting | |
Office hours: by appointment | ||
Room 2.019 Kollegiengebäude Mathematik (20.30) | ||
Email: tilmann.gneiting@kit.edu | Problem classes | Dipl.-Math. oec. Markus Scholz |
Office hours: Tuesday, 10:30-11:30 o'clock | ||
Room 2.010 Kollegiengebäude Mathematik (20.30) | ||
Email: ma.scholz@kit.edu |
Content
A time series is a set of data in which the subscript
indicates the time at which the datum was observed. The course
provides an introduction to the theory and practice of statistical
time series analysis. Topics covered include stationary and
non-stationary stochastic processes, autoregressive and moving average
(ARMA) models, state-space models and Kalman filter, model selection
and estimation, forecasting and forecast assessment, and an outline
of spectral techniques.
Statistical Software for Time Series Data
The problem sets will frequently require the use of a suitable
statistical programming language. Any code discussed in class
meetings will be written in the R language, and you are encouraged to
use R, or your standard language if it is suitable.
ILIAS Course
Course Material and important information can be found in the ILIAS course of the lecture.
Examination
There will be oral examinations towards the end of the semester. All further details can be found in the ILIAS course of the lecture.
References
- Brockwell, P. J. and Davis, A. (2006). Time Series, Theory and
Methods, second edition. New York: Springer.
- Brockwell, P. J. and Davis, A. (2010). Introduction to Time
Series and Forecasting, second edition. New York: Springer.
- Chatfield, C. (2004). The Analysis of Time Series, an
Introduction, sixth edition. London: Chapman & Hall/CRC.
- Diggle, P. J. (2004). Time Series, a Biostatistical
Introduction. Oxford: Clarendon Press.
- Shumway, R. H. and Stoffer, D. S. (2011). Time Series Analysis
and Its Applications: With R Examples, third edition. New York:
Springer.
- Venables, W. N. and Ripley, B. D. (2004). Modern Applied
Statistics with S-PLUS, fourth edition. New York: Springer.
- Wei, W. W. S. (2006). Time Series Analysis, Univariate and
Multivariate Methods, second edition. Boston: Pearson Addison
Wesley.
- Zivot, E. and Wang, J. (2006). Modeling Financial Time Series
With S-Plus, second edition. New York: Springer.