Time Series 2E

By Wayne A. Fuller

The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter.

Major topics include:
* Moving average and autoregressive processes
* Introduction to Fourier analysis
* Spectral theory and filtering
* Large sample theory
* Estimation of the mean and autocorrelations
* Estimation of the spectrum
* Parameter estimation
* Regression, trend, and seasonality
* Unit root and explosive time series

To accommodate a wide variety of readers, review material, especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.

• Format: Hardcover
• Language: English
• ISBN: 0471552399
• ISBN13: 9780471552390
• Release Date: December 1995
• Publisher: Wiley & Sons, Incorporated, John
• Length: 728 Pages
• Weight: 2.51 lbs.
• Dimensions: 1.8" x 6.4" x 9.6"

Customer Reviews

excellent graduate text covering both time and frequency domain methods

In 1981 I used this book for a graduate seminar that I taught on time series analysis at UC Santa Barbara. The course was successful because I followed the text closely. It presents the material in a rigorous and cogent manner. At the time there were a few competing books but some emphasized time domain methods and others were strictly frequency domain approaches. Fuller balances the two very well and his book is better written and organized than most of the competitors at that time (1981). Today there are a lot more books to choose from. You can check my listmania list on time series books to get an idea. I particularly like Brockwell and Davis' book as a competitor to Fuller for a graduate level time series seminar.