The course STOR 754 is one of the Statistics program's "B-level" courses. Students in the Statistics program will have already taken the first-year or "A-level" courses. Students from other programs are welcome to take the course provided they have had roughly the following background: a graduate-level course in regression and linear models equivalent to STOR 664; and some exposure to graduate-level statistical theory at the level of the STOR 654/655. If in doubt, please email the instructor.

Required text: Time Series: Theory and Methods (Springer Series in Statistics) by Peter J. Brockwell, Richard A. Davis

Recommended text: Multivariate Analysis (Probability and Mathematical Statistics) (Paperback) by K.V. Mardia, J.T. Kent and J.M. Bibby.

These will be supplemented by the instructor's own course notes - for the current version of these (produced in 1999), please see the course website. I may update these as the course proceeds.

Class announcements, homework assignments and any changes in schedule will be posted on this website.

The first class is on Tuesday, August 19 and the last class is on Tuesday, December 2. There will be no class on Thursday, October 16 because of Fall Break or on Thursday, November 27 because of Thanksgiving. The final exam is fixed by the University Registrar for Thursday, December 12 at noon. There is a possibility that I may decide the replace the final exam by a take-home final, but unless announced otherwise, please assume that is the time of the final exam and do not schedule any activities for yourself that are in conflict with that.

In addition to the final exam, there will be homeworks at roughly two-week intervals, and a midterm exam. The midterm is tentatively schedule for Tuesday, October 14 ; however, I have more flexibility to change that than I do for the final exam, so please let me know if you foresee any conflict at that time.

Topics, Time series: Stationary processes; autocovariances, spectral density, linear process, ARMA. Estimation, time and spectral domain methods. Prediction.

Topics, Multivariate analysis: Basic theory of the multivariate normal and Wishart distributions. Principal components, canonical correlations, factor analysis, cluster analysis.

Other topics that may be covered as time permits: Multivariate time series, state space models, long-range dependence, dimension-reduction techniques in multivariate analysis.

Software: The Brockwell-Davis book includes an excellent self-contained (and very user-friendly) time series package called ITSM, and part of the time we will use that. However, R also includes extensive facilities for both time series and multivariate analysis, so we will use that as well. No previous knowledge of ITSM is needed; some previous exposure to R is desirable but not essential. If you don't know R already you can download it from http://www.r-project.org. The course notes include programs in S-PLUS, but where necessary, we will update these to run in R. S-PLUS will not be used in this course.

Special Note: B-level courses are normally taught once every two years, but this schedule is not followed exactly. The last time STOR 754 was taught was Spring 2008, when the instructor was Professor P.K. Sen. It is my understanding that Professor Sen concentrated on the "Multivariate" half of the course. Given this background, my intention is to spend at least two-thirds of the class time on time series, though the exact amount may depend on how many students who register for this class also took STOR 754 in the spring. Direct overlap between the two courses will be kept to a minimum. Therefore, it has been agreed that students who previously took STOR 754 with Professor Sen are allowed (and encouraged) to take it a second time to learn about time series.

You are reminded that the university Honor Code is in effect for this course. For homework assignments, you are allowed to discuss the problems among yourselves, but the work you hand in must be your own; direct copying is not permitted. For exams, whether in-class or take-home, you are expected to work the problems entirely by yourselves and consultation of any kind is forbidden, unless it is with me or the Instructional Assistant (if we have one).