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| STAT 52000 - Time Series And Applications |
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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.
3.000 Credit hours Syllabus Available Levels: Undergraduate, Graduate, Professional Schedule Types: Distance Learning, Lecture Offered By: College of Science Department: Statistics Course Attributes: Upper Division May be offered at any of the following campuses: PU Fort Wayne IUPUI West Lafayette 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. Restrictions: May not be enrolled as the following Classifications: Sophomore: 45 - 59 hours Sophomore: 30 - 44 hours Freshman: 0 - 14 hours Freshman: 15 - 29 hours Prerequisites: GR-STAT 51600 Course General Requirements: ( Student Attribute: GR May not be taken concurrently. ) or ( Course or Test: STAT 51200 Minimum Grade of D- May not be taken concurrently. ) |
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