STAT223: Time Series Analysis

Graduate level introductory course on time series data and models in the time and frequency domains: descriptive time series methods; the periodogram; basic theory of stationary processes; linear filters; spectral analysis; time series analysis for repeated measurements; ARIMA models; introduction to Bayesian spectral analysis; Bayesian learning, forecasting, and smoothing; introduction to Bayesian Dynamic Linear Models (DLMs); DLM mathematical structure; DLMs for trends and seasonal patterns; and autoregression and time series regression models.

5 credits

Year Fall Winter Spring Summer

Formerly AMS 0223

While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.