STAT 52000 - Time Series And Applications

Credit Hours: 3.00.  An introductory course in stationary time series with applications. Topics include stationarity, autocovariance function, ARIMA (Autoregressive Integrated Moving Average) models, and basic spectral analysis (periodograms and their estimation, tapering, linear filtering). Extensive use of R is incorporated for building time series models and estimating the time series spectrum.

Learning Outcomes
1. Recognize basic properties of stationary time series and various aspects and representations of ARMA and ARIMA models.
2. Understand and apply standard time domain techniques for the identification, estimation, and forecasting of ARIMA models.
3. Identify elementary concepts and techniques for spectral analysis.
4. Use R facilities to analyze real life time series data.

Credits: 3.00

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STAT 52000 - Time Series And Applications