Time series regression. Nonstationary and stationary time series models. Nonseasonal and seasonal time series models. ARIMA (Box-Jenkins) models. Smoothing methods. Parameter estimation, model identification, diagnostic checking. Forecasting techniques. A statistical software package will be used. Prerequisite(s): STAT 3553 or STAT 3503, or permission of the School.Lectures three hours a week, laboratory one hour a week.
Time series regression. Nonstationary and stationary time series models. Nonseasonal and seasonal time series models. ARIMA (Box-Jenkins) models. Smoothing methods. Parameter estimation, model identification, diagnostic checking. Forecasting techniques. A statistical software package will be used. Prerequisite(s): STAT 3553 or STAT 3503, or permission of the School.Lectures three hours a week, laboratory one hour a week.