Department of Statistics

Current Sections   Recent Instructors Bloomfield, P	ST 730	Applied Time Series Analysis
	Course Description An introduction to use of statistical methods for analyzing and forecasting data observed over time. Trigonometric regression, periodogram/spectral analysis. Smoothing. Autoregressive moving average models. Regression with autocorrelated errors. Linear filters and bivariate spectral analysis. Stress on methods and applications; software implementations described and used in assignments. Course Syllabus Review of Statistical Methods Runs Test Trigonometric Regression Periodogram and Spectral Analysis Autoregressive Models ARMA Models Seasonal ARMA Linear Filters Bivariate Spectral Analysis Nonstationarity Regression with AR Errors Transfer Functions Vector AR Cointegration Course Prerequisites ST430 or ST507 or ST511 or ST515 ST514 or ST508 or ST512 or ST516 Course Corequisites None Recent Textbooks SAS for Forecasting Time Series 2nd ed, by John C. Brocklebank and David A. Dickey (2003)