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Stat 131 Time Series Analysis: Introductory Examples

Stat 131 Time Series Analysis: Introductory Examples. Instructor : Jose Blanchet (Science center 606) Instructor’s office hours (tentative): Mon 2:15 – 3:15 PM & Wed 5:45 – 6:45 PM TF: Wei Zhang Office hours: TBA.

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Stat 131 Time Series Analysis: Introductory Examples

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  1. Stat 131Time Series Analysis: Introductory Examples

  2. Instructor: Jose Blanchet (Science center 606) Instructor’s office hours (tentative): Mon 2:15 – 3:15 PM & Wed 5:45 – 6:45 PMTF: Wei ZhangOffice hours: TBA

  3. www.courses.fas.harvard.edu/~stat131/Primary text: Brockwell, P., and Davis, R. (1991) Time Series: Theory and Methods. 2nd edition, Springer.Secondary: Brockwell, P. and Davis, R. (2002) Introduction to Time Series and Forecasting. 2nd edition. Springer.

  4. Description: • Model building, data analysis, inference and forecasting using Auto regressive (AR), moving average (MA), ARMA, and ARIMA processes. • Stationary and non-stationary processes, seasonal processes, auto-correlation and partial auto-correlation functions, identification of models, estimation of parameters, and spectral analysis. • Prerequisite: Stat 110, recommended Stat 111 and/or Stat 139.

  5. Grading Policy • Homework 20% (About 6 problems sets) • May discuss homework problems with other students, but must write them up independently. • Correct answers without supporting work will not receive credit. • Homework is due at the beginning of class on the due date. Late homework will not be accepted. • Your lowest homework score will be dropped when computing your final grade… (i.e. this leaves room for emergencies!) • SOME HOMEWORKS WILL REQUIRE USE OF MATLAB OR ANY OTHER COMPUTER PACKAGE…

  6. Examples of Time Series • Monthly sales of red wine (in liters) of an Australian wine maker MONTLY from January 1980 to October 1991

  7. Examples of Time Series • Monthly sales of red wine (in liters) of an Australian wine maker MONTLY from January 1980 to October 1991

  8. Examples of Time Series • Monthly accidental deaths data 1973 to 1978 measured in thousands of dollars… (seasonal components)

  9. Examples of Time Series

  10. Mean reversion of heights of individuals across generations… (Galton and Pearson)

  11. Additional important applications: • Financial time series… • Economic variables such as inflation, exchange rates… • Engineering: linear and non-linear time series, queueing theory, signal processing…

  12. General objective: • Given a random process identify trend, seasonality and noise (randomness) • Estimate the structure of the standardize (without trend and seasonality) series… • Analysis and forecasting…

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