Syllabus
Rutgers University
College of Engineering
Department of Industrial Engineering
540:682 Process Modeling and Control
Instructor: Dr. M. B. Gürsoy
Office: CoRE 218
Phone: X-5465
Email: gursoy@soe.rutgers.edu
COURSE OUTLINE
 
    • Introduction to Time Series Modeling
    • Autocorrelation Function and Spectral Properties of Stationary Processes
    • Linear Stationary Models – AR, MA, ARMA
    • Linear Nonstationary Models – IMA, ARIMA
    • Forecasting: Minimum Mean Square Forecast, ARMA, ARIMA models, State Space Models, Kalman Filtering
    • Model Identification – Autocorrelation, Partial Autocorrelation Functions, Initial Estimates, unit root test
    • Model Estimation – Likelihood Function, Least Squares Estimates
    • Model Diagnostic Checking
    • Seasonal Models
    • Transfer Function Models – Linear Transfer Function, Discrete Dynamic Models
    • Aspects of Process Control – Process Monitoring, Feedback Control, MMSE Control

Text:

Time Series Analysis, by G. E. P. Box, G. M. Jenkins and G. C. Reinsel, Prentice Hall, 3rd Edition, 1994.

References: Introduction to Time Series and Forecasting, by P. J. Brockwell and R. A. Davis, 2nd Edition, Springer 2002.

Time Series: Theory and Methods, by P. J. Brockwell and R. A. Davis, Springer, 2nd Edition, 1991.

Introduction to Statistical Time Series, by W. A. Fuller, 2nd Edition, Wiley and Sons, 1996.