MAST 667
Reading Course in Analysis
Winter 2023 · Time Series and Forecasting
Topics
- Time-series models, trends and seasonality
- Stationary processes and autocorrelation
- Linear and ARMA processes
- Forecasting stationary series and Wold decomposition
- ARMA autocorrelation and partial autocorrelation
- Spectral densities and periodograms
- Time-invariant linear filters
- Parameter estimation and maximum likelihood
- Diagnostic checking, model order selection and forecasting
Readings
- Listed textbook (requirement not stated): Peter J. Brockwell and Richard A. Davis. Introduction to Time Series and Forecasting, 3rd edition. Springer, 2016.
- Reference (not explicitly required): Chris Chatfield. The Analysis of Time Series: An Introduction with R, 7th edition. Chapman & Hall/CRC, 2019.
- Reference (not explicitly required): Robert H. Shumway and David S. Stoffer. Time Series Analysis and Its Applications, 4th edition. Springer, 2017.
Winter 2022 · STAT 460
Readings
- Introduction to Time Series and Forecasting, 3rd Edition, by Peter J. Brockwell and Richard A. Davis, Springer, 2016.
- The Analysis of Time Series: An Introduction with R, 7th Edition, by Chris Chatfield, Chapman & Hall/CRC, 2019.
- Time Series Analysis and Its Applications, 4th Edition, by Robert H. Shumway and David S. Stoffer, Springer, 2017.
Sources
- Course catalogue ↗2026–2027
- Syllabus or course outline ↗Winter 2023
- Historical course outline ↗Winter 2022
- Winter 2023 outline. Course header explicitly lists STAT 460, MAST 667, MAST 881. First-page header lists STAT 460 (MAST 667/MAST 881), while the later footer says MAST 677. The MAST 667 code is retained as printed in the first-page header, with this unresolved source inconsistency flagged.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.