(3 cr.) P: Two statistics courses at the graduate level, or consent
of instructor. Techniques for analyzing data collected at different
points in time. Probability models, forecasting methods, analysis in
both time and frequency domains, linear systems, state-space models,
intervention analysis, transfer function models and the Kalman
filter. Topics also include: Stationary processes, autocorrelations,
partial autocorrelations, autoregressive, moving average, and ARMA
processes, spectral density of stationary processes, periodograms
and estimation of spectral density.