Description

Book 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 accom

Table of Contents
Moving Average and Autoregressive Processes.

Introduction to Fourier Analysis.

Spectral Theory and Filtering.

Some Large Sample Theory.

Estimation of the Mean and Autocorrelations.

The Periodogram, Estimated Spectrum.

Parameter Estimation.

Regression, Trend, and Seasonality.

Unit Root and Explosive Time Series.

Bibliography.

Index.

Time Series 2E 230 Wiley Series in Probability

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    A Hardback by Wayne A. Fuller

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      View other formats and editions of Time Series 2E 230 Wiley Series in Probability by Wayne A. Fuller

      Publisher: John Wiley & Sons Inc
      Publication Date: 04/04/1996
      ISBN13: 9780471552390, 978-0471552390
      ISBN10: 0471552399

      Description

      Book 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 accom

      Table of Contents
      Moving Average and Autoregressive Processes.

      Introduction to Fourier Analysis.

      Spectral Theory and Filtering.

      Some Large Sample Theory.

      Estimation of the Mean and Autocorrelations.

      The Periodogram, Estimated Spectrum.

      Parameter Estimation.

      Regression, Trend, and Seasonality.

      Unit Root and Explosive Time Series.

      Bibliography.

      Index.

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