Statistics 16:960:565 Applied Time Series Analysis
Schedule
The course is normally offered during the Spring semester.- Class meeting dates: Please visit the University's academic calendar.
- Schedule and Instructor: Please visit the University's schedule of classes for the instructor, time, and room.
- Instructor and Teaching Assistant Office Hours: Please visit the Mathematical Finance program's office hour schedule.
Course Abstract
Model based forecasting methods, autoregressive and moving average models, ARIMA, ARMAX, ARCH, state-space models, estimation, forecasting and model validation, missing data, irregularly spaced time series, parametric and non-parametric bootstrap methods for time series, multi-resolution analysis of spatial and time series signals, time-varying models and wavelets.Pre-requisites
Statistics 16:960:563 (Regression Analysis).Primary Textbooks
Required: Brockwell, P., Davis, A. Introduction to Time Series and Forecasting . 2nd edition, Springer.Suggested: Shumway, R., Stoffer, D. S., Time Series Analysis and Its Applications.
Suggested: Venables and Ripley , Modern Applied Statistics with Splus.
Grading
Please contact the instructor.Class Policies
Please contact the instructor.Previous Course Instructor Websites
Rebecka JornstenWeekly Lecturing Agenda and Readings
| Lecture | Topics | Reading Assignments |
|---|---|---|
| 1 | Introduction, Stationary Processes | 1.1-1.6, 2.1-2.2 |
| 2 | Stat. Processes, Measures of Dependence, Tests of Randomness | 2.1-2.4, 1.4, 1.6 |
| 3 | Forecasting | 2.5,3.1-3.3 |
| 4 | Spectral methods | 4.1-4.4 |
| 5 | Spectral methods | 4.1-4.4 |
| 6 | Review, Estimation | 5.1-5.2 |
| 7 | Estimation, Model selection. | 5.2-5.5 |
| 8 | ARIMA/ SARIMA | 6.1-6.3 |
| 9 | Multivariate | 7.1-7.7 |
| 10 | Multivariate, Bootstrap | 7.1-7.7, handout |
| 11 | Smoothing, Image processing | handout |
| 12 | Wavelets | handout |
| 13 | State-Space | 8.1-8.7 |
| 14 | Wrap-up, new methods | handout, 9.2 |
