AS/SC/ MATH 4130B 3.0 F
Same as GS/MATH 6630 3.0

Topics in Probability and Statistics:
Introduction to the Theory and Methods
of Time Series Analysis

      A systematic presentation of many statistical techniques for the analysis of time series data. The core topics include time dependence and randomness, trend, seasonality and error, stationary processes, ARMA and ARIMA processes, multivariate time series models and state-space models.
      An additional topic is forecasting. The emphasis is on the theory and methodology of the time-domain analysis based on ARIMA and state-space models. An important component of the course is that the analysis of data sets is illustrated throughout. interpretation of the results obtained on some assigned problems.
      The text is P.J. Brockwell and R.A. Davis, Introduction to Time Series and Forecasting, Springer--Verlag. Some materials from P.J. Brockwell and R.A. Davis, Time Series: Theory and Methods, Springer--Verlag, are imported as necessary.
      The course will be evaluated by assignments, one midterm, and a final exam.