Statistics 451 - Applied Time Series
Instructor: William Q. Meeker, 294-5336
Instructor email: firstname.lastname@example.org
Office Hours: WF 2:10-3:00 p.m. in 2109 Snedecor Hall (or by appointment---send email)
Lecture: MWF 12:10-1:00, Gilman 2205
Assignments: Due weekly on Fridays, unless announced otherwise.
Examinations: Two one-hour exams plus a two-hour final examination.
Statistics 451 homepage:
Text: None required; see suggested reading below
Class Notes: Available from the course webpage.
Upon successful completion of this course, students will understand the nature of time series data and the structure of various time series models for stationaty, nonstationary, and seaconal time series. They will be able to identify an appropriate time series model, fit such models to data, and use the models for purposes of forecasting, including quantification of forecast errors through the construction of prediction intervals. Students will understand how to extend univariate models to allow for the use of explanatory varialbes to model both interventions and transfer functions.
R and RTSERIES
Time Series Analysis and Forecasting by Example by Soren Bisgaard and Murat Kulahci, John Wiley and Sons.
Time series analysis and its applications. Shumway, R. H., & Stoffer, D. S. (2013). Springer Science & Business Media.
Time Series Analysis - Univariate and Multivariate Methods (Second Edition) by William W.S.Wei
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