ISYE 431 Time Series Forecasting
The objective of this course is to teach the students how to model and forecast time series data, using specialized statistical techniques and software. The emphasis will be on the time domain. Topics include: regression analysis, exponential smoothing methods, stationarity, time series specification, decomposition and the Box-Jenkins methods, ARMA/ARIMA, SARIMA models, model estimation, multi-step ahead forecast and forecast error. This course will provide students with hands-on experience in techniques for modeling and prediction of time series.
Prerequisite
MATH 213, MATH 242
Offered
Fall