SYDE 631 Time Series Modelling
SYDE 631 - TIME SERIES MODELLING
Fall Term
PURPOSE: The theory and practice of time series modelling are presented for systematically studying observations sampled over time from water resources, environmental, economical, energy and other kinds of systems. By understanding, for example, how inputs to a given system dynamically affect various outputs, better decisions can be made regarding the design and operation of the system.
COURSE OUTLINE: The rich variety of time series models that are defined, explained and illustrated in the course include ARMA, nonstationary ARIMA, long memory FARMA, seasonal ARIMA, deseasonalized, periodic, transfer function-noise (multiple inputs - single output), intervention and multivariate ARMA (multiple inputs - multiple outputs) models. Extensive hydrological, water quality, environmental, and other applications are given for clearly demonstrating how the various kinds of time series models can be systematically and conveniently fitted to real world data sets by following the identification, estimation and diagnostic check stages of model construction. Moreover, a major emphasis of the course is the use of exploratory data analysis graphs, intervention analysis, nonparametric trend tests and regression analysis in the detection and estimation of trends in environmental impact assessment studies. Other topics covered include time series analysis in decision making, estimating missing observations, simulation, the Hurst Phenomenon, forecasting experiments and causality.
COURSE TEXT: Time Series Modelling of Water Resources and Environmental Systems, by Keith W. Hipel and A. Ian McLeod, published by Elsevier, Amsterdam, 1994 (ISBN: 0 444 89270-2). To download a copy of the book please click Time Series Modelling of Water Resources and Environmental Systems by Keith W. Hipel & A. Ian McLeod, © 2005 by Hipel and McLeod.
OVERHEAD NOTES: Students can concentrate on the joy of learning in class by obtaining advance copies of overhead projector notes which put the entire course into proper perspective.
DECISION SUPPORT SYSTEM (DSS): The McLeod-Hipel Time Series (MHTS) Package constitutes a flexible DSS for carrying out comprehensive data analysis studies in order to obtain meaningful statistical results upon which wise decisions can be made. Each student will be able to use the MHTS package in course assignments and a project consisting of data analyses of time series chosen from the field of interest of the student.
PRE-REQUISITE COURSE: At least one university course in probability and statistics.
GRADING: Course assignments, a project selected according to a given student’s interest, and a final examination will account for 10%, 30% and 60%, respectively, of the final grade.
CLASS TIME: Every Monday during the fall term from 1:30 p.m. to 4:30 p.m. in E2 1307C.
INFORMATION: If you have any questions please contact the class instructor, Professor Keith W. Hipel, in the Department of Systems Design Engineering (Room E2 1307D; 519-888 4567, extension 32830; kwhipel@uwaterloo.ca). Students are most welcome to take the course for credit or audit. Certain components of the courses will be tailored to meet the background and interests of the students.