Introduction to Statistical Time Series (Wiley Series in Probability and Statistics) - Hardcover

Fuller, Wayne A.

Hardcover

ISBN 10: 0471552399 ISBN 13: 9780471552390

Publisher: Wiley-Interscience, 1995

Synopsis

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.

About this title

About the Author

WAYNE A. FULLER is Distinguished Professor in the Departments of Statistics and Economics at Iowa State University. He is the author of Measurement Error Models and numerous articles in time series, survey sampling, and econometrics. A Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Econometric Society, he received his PhD in agricultural economics from Iowa State University.

From the Back Cover

The subject of time series is of considerable interest, especially among researchers in econometrics, engineering, and the natural sciences. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new Second Edition, covers the important advances of recent years, including nonstationary models, nonlinear estimation, multivariate models, state space representations, and empirical model identification. New sections have also been added on the Wold decomposition, partial autocorrelation, long memory processes, 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 sample statistics, and difference equations, has been included.

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 sample statistics, and difference equations, has been included.

Edition details

• Publisher: Wiley-Interscience
• Publication date: 1995
• Language: English
• ISBN 10: 0471552399
• ISBN 13: 9780471552390
• Binding: Hardcover
• Edition number: 2
• Number of pages: 728