STA 5250 - Time Series Analysis (3)

Difference equations. Stationary and non-stationary models. Autocorrelation and partial autocorrelation functions. Autoregressive (AR), Moving average (MA), Autoregressive-moving average (ARMA), and Autoregressive integrated moving average (ARIMA) models. Models for seasonal time series. Identification, estimation, diagnostic checking and forecasting. Use of computer package such as SAS or MINITAB or R.

Prerequisite(s): STA 2260, STA 326, IME 3140, IME 314, or STA 2100 and STA 2200.
Component(s): Lecture
Grading Basis: Graded Only
Repeat for Credit: May be taken only once