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Analysis and time series: an introduction with R/ Chris Chatfield and Haipeng Xing

By: Contributor(s): Series: Texts in Statstical SciencePublication details: Boca Raton: CRC Press, 2019Edition: 7thDescription: xv, 308 pages, 24 cmISBN:
  • 9781138066137
Subject(s): DDC classification:
  • 23 SA.3 C492
Contents:
Introduction -- Basic descriptive techniques -- Some linear time series models -- Fitting time series models in the time domain -- Forecasting -- Stationary processes in the frequency domain -- Spectral analysis -- Bivariate processes -- Linear systems -- State-space models and the Kalman filter -- Non-linear models -- Volatility models -- Multivariate time series modelling -- Some more advanced topics --
Summary: This edition presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.
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Includes bibliography and index

Introduction -- Basic descriptive techniques -- Some linear time series models -- Fitting time series models in the time domain -- Forecasting -- Stationary processes in the frequency domain -- Spectral analysis -- Bivariate processes -- Linear systems -- State-space models and the Kalman filter -- Non-linear models -- Volatility models -- Multivariate time series modelling -- Some more advanced topics --

This edition presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.

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