Introduction to Statistical Time Series

Wayne A Fuller

ISBN 10: 0471552399 / ISBN 13: 9780471552390

Published by Wiley Dez 1995, 1995

About this Item

Neuware - 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.

Seller Inventory # 9780471552390

Bibliographic Details

• Title: Introduction to Statistical Time Series
• Publisher: Wiley Dez 1995
• Publication Date: 1995
• Language: English
• ISBN 10: 0471552399
• ISBN 13: 9780471552390
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 240W x 161H x 43D millimeters 240 millimeters width by 161 millimeters height by 43 millimeters depth
• Weight: 1252 grams

About this title

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 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.