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- Author: Fuller
- Publisher: John Wiley & Sons
- ISBN-10: 0471552399
- ISBN-13: 9780471552390
- Format: 16.3 x 24.4 x 4.5 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
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.
EXTRA 10 % discount with code: EXTRA
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- Author: Fuller
- Publisher: John Wiley & Sons
- ISBN-10: 0471552399
- ISBN-13: 9780471552390
- Format: 16.3 x 24.4 x 4.5 cm, kieti viršeliai
- Language: English English
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.
Reviews