This book provides a comprehensive introduction to the theory and practice of time series analysis. Topics include:
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This book provides a comprehensive introduction to the theory and practice of time series analysis. Topics include:
This book provides a comprehensive introduction to the theory and practice of time series analysis. A wide range of topics is covered including ARIMA probability models, forecasting methods (including exponential smoothing and Box-Jenkins), spectral analysis, linear systems, state-space models and the Kalman filter. This edition includes additional chapters on non-linear models (incorporating material on neural nets and chaos) and multivariate models (including VARMA models) as well as additional examples and references to topics such as wavelets and long-memory models.
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