STAT 673 (MWF - 16:10-17:00)

Instructor: Suhasini Subba Rao (office: Blocker 435).

Here is the Handout and Syllabus.

This is a theory and methods based course (with an emphasis on theory).

All typos and mistakes in these notes are my responsibility. If you use these notes, please acknowledge them.

• All notes
• Preface
• Introduction (Chapter 1)
• Linear Time Series Models (Chapter 2)
• Prediction (Chapter 3)
• Estimation (Chapter 4)
• Methods for deriving sampling properties (Chapter 5)
• Sampling properties of the ARMA estimators defined in Chapter 4 (Chapter 6)
• The residual bootstrap for AR models (Chapter 7)
• Spectral Analysis for Time Series (Chapter 8)
• Nonlinear Time Series (Chapter 9)
• Nonstationary Time Series (Chapter 10)

  Further reading: Here is a scanned version of Tata Subba Rao's book, on nonlinear time series An Introduction to Bispectral Analysis and Bilinear Time Series Models By Tata Subba Rao and M. M. Gabr.

• Mixingale methods. This is the last chapter and describes how mixingales can be used in asymptotic analysis. It is an optional component in the course. These notes will need to be updated and corrected.
• spectral densities
• A review of cumulants
• Preliminaries (Appendix)
• Bibliography

Some links to help you:

MathSciNet