Statistics 451 - Applied Time Series
Spring 2013

Instructor: William Q. Meeker, 294-5336
Instructor email: wqmeeker@iastate.edu
Office Hours: MTRF 2:10-3:00 p.m. in 2019 Snedecor Hall (or by appointment---send email)
Lecture: MWF 12:10-1:00, Sweeney 1126
Assignments: Due weekly on Fridays, unless announced otherwise.
Examinations: Two one-hour exams plus a two-hour final examination.

Statistics 451 homepage: http://www.public.iastate.edu/~stat451
Text:
Class Notes: Available from the course homepage.

Tentative Schedule

1. Introduction to time series and time series models. (Handout 1 and Chapters 1 and 2, 2 days)
2. Review of multiple regression and descriptive methods, and further introduction to time series analysis. (Handout 1A; 6 days) Graphical techniques, transformations, analysis of residuals, autocorrelation.
3. Fundamental concepts of time series modleing. (Handout 2, Chapters 1 and 3; 10 days) Stochastic processes, process and sample autocorrelation function, partial autocorrelation function.
4. Stationary time series models. (Handouts 3 and 4, Chapter 3; 6 days) ARIMA models, model identification. Nonstationary time series. (Handout 5, Chapter 4; 3 days) Differencing, transformation, identification.
5. Estimation in time series. (Handout 6; 2 days) Nonlinear least squares, potential problems, diagnostic checking and residual analysis.
7. Forecasting and prediction intervals. (Handout 7, Chapters 4 and 5; 4 days)
8. Seasonal time series models. (Handout 8, Chapter 5; 3 days) SARIMA models, identification, estimation, forecasting.
9. Transfer function and intervention models. (Handouts 9 and 10, Chapters 8; 11 days)
10. Vector (multivariate) time series. (Chapter 9, notes; 3 days)

Supplementary Reading:
Time Series Analysis: Forecasting and Control by G.E.P. Box and G.M. Jenkins
Practical Experiences with Modeling and Forecasting Time Series by G.M. Jenkins

Click here to go to W.Q. Meeker's homepage.