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Preface to the Sixth Edition | |
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Abbreviations and Notation | |
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Introduction | |
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Some Representative Time Series | |
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Terminology | |
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Objectives of Time-Series Analysis | |
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Approaches to Time-Series Analysis | |
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Review of Books on Time Series | |
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Simple Descriptive Techniques | |
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Types of Variation | |
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Stationary Time Series | |
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The Time Plot | |
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Transformations | |
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Analysing Series that Contain a Trend | |
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Analysing Series that Contain Seasonal Variation | |
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Autocorrelation and the Correlogram | |
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Other Tests of Randomness | |
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Handling Real Data | |
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Some Time-Series Models | |
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Stochastic Processes and Their Properties | |
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Stationary Processes | |
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Some Properties of the Autocorrelation Function | |
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Some Useful Models | |
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The Wold Decomposition Theorem | |
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Fitting Time-Series Models in the Time Domain | |
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Estimating Autocovariance and Autocorrelation Functions | |
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Fitting an Autoregressive Process | |
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Fitting a Moving Average Process | |
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Estimating Parameters of an ARMA Model | |
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Estimating Parameters of an ARIMA Model | |
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Box-Jenkins Seasonal ARIMA Models | |
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Residual Analysis | |
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General Remarks on Model Building | |
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Forecasting | |
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Introduction | |
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Univariate Procedures | |
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Multivariate Procedures | |
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Comparative Review of Forecasting Procedures | |
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Some Examples | |
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Prediction Theory | |
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Stationary Processes in the Frequency Domain | |
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Introduction | |
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The Spectral Distribution Function | |
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The Spectral Density Function | |
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The Spectrum of a Continuous Process | |
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Derivation of Selected Spectra | |
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Spectral Analysis | |
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Fourier Analysis | |
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A Simple Sinusoidal Model | |
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Periodogram Analysis | |
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Some Consistent Estimation Procedures | |
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Confidence Intervals for the Spectrum | |
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Comparison of Different Estimation Procedures | |
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Analysing a Continuous Time Series | |
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Examples and Discussion | |
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Bivariate processes | |
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Cross-Covariance and Cross-Correlation | |
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The Cross-Spectrum | |
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Linear Systems | |
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Introduction | |
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Linear Systems in the Time Domain | |
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Linear Systems in the Frequency Domain | |
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Identification of Linear Systems | |
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State-Space Models and the Kalman Filter | |
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State-Space Models | |
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The Kalman Filter | |
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Non-Linear Models | |
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Introduction | |
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Some Models with Non-Linear Structure | |
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Models for Changing Variance | |
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Neural Networks | |
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Chaos | |
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Concluding Remarks | |
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Bibliography | |
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Multivariate Time-Series Modelling | |
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Introduction | |
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Single Equation Models | |
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Vector Autoregressive Models | |
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Vector ARMA Models | |
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Fitting VAR and VARMA Models | |
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Co-integration | |
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Bibliography | |
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Some More Advanced Topics | |
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Model Identification Tools | |
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Modelling Non-Stationary Series | |
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Fractional Differencing and Long-Memory Models | |
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Testing for Unit Roots | |
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Model Uncertainty | |
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Control Theory | |
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Miscellanea | |
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Examples and Practical Advice | |
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General Comments | |
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Computer Software | |
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Examples | |
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More on the Time Plot | |
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Concluding Remarks | |
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Data Sources and Exercises | |
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Fourier, Laplace and z-Transforms | |
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Dirac Delta Function | |
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Covariance and Correlation | |
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Some MINITAB and S-PLUS Commands | |
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Answers to Exercises | |
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References | |
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Index | |