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Jul 30, 2025
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CSCI 6240 - Time Series Analysis
Time series (TS) are found in a wide range of applications, including economics and finance, biomedical domains, etc. This course introduces the theory and practice of statistical TS analysis. We study how TS data are sampled and how to resample, which relates to the missing data problem. We also analyze TS data to identify deterministic and nondeterministic components, fitting a model to such data for prediction. Topics covered include stationary and non-stationary stochastic processes, autoregressive and moving average (ARMA) models, state-space models and the Kalman filter, forecasting and forecast evaluation, and an outline of spectral techniques. We also cover deep neural networks relevant to TS data, including RNN and LSTM. Course activities include programming and analytical assignments, a term project with a presentation, and exams.
Prerequisite or Corequisite: None.
When Offered: SPRING TERM ANNUALLY
Co-Listed: CSCI 4240
Graded: GRADED
Credit Hours: 4
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