Stat 520: Time Series and Applications (Banner Course Number: 52000)

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Spring 2010 textbook will be:

For Zhang, Hao -- Cryer and Chan, Time Series Analysis: With Applications in R (electronic copy available here: http://www.springerlink.com/content/w88341/), 2008 Edition, Required

Outline:

  1. Stationary time series: weak and strict stationarity, the autocovariance function, estimation and elimination of trend and seasonal components

  2. Prediction of stationary processes: the orthogonality principle and projections, best linear predictors

  3. Estimation of the mean and autocovariance function: point estimates and confidence intervals for the mean, point estimates and confidence intervals for the autocovariance function

  4. Estimation of the spectral density: the periodogram and its properties, smoothing the periodogram, point estimates and confidence intervals for the spectral density

  5. Estimation for ARMA models: the Yule-Walker equations for AR processes, the Durbin-Levinson algorithm, maximum likelihood and least squares estimates, choosing the order of the model