Time Series Analysis 3E
Focuses on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
Includes a considerably revised chapter on estimation of ARMA models.
Features new sections on: Recently developed methods for model specification, such as canonical correlation analysis and the use of model selection criteria.
Results on testing for unit root nonstationarity in ARIMA processes.
The state space representation of ARMA models and its use for likelihood estimation and forecasting. Score test for model checking. Deterministic components and structural components in time series models and their estimation based on regression-time series model methods
Adds a chapter on intervention and outlier analysis. Provides completely rewritten material on control - to reflect the new emphasis on industrial quality improvement and the role of control both in process monitoring as well as in process adjustment.
I. STOCHASTIC MODELS AND THEIR FORECASTING.
2. The Autocorrelation Function and Spectrum of Stationary Processes.
3. Linear Stationary Models.
4. Linear Nonstationary Models.
II. STOCHASTIC MODEL BUILDING.
6. Model Identification.
7. Model Estimation.
8. Model Diagnostic Checking.
9. Seasonal Models.
III. TRANSFER FUNCTION MODEL BUILDING.
10. Transfer Function Models.
11. Identification, Fitting, and Checking of Transfer Function Models.
12. Intervention Analysis Models and Outlier Detection.
IV. DESIGN OF DISCRETE CONTROL SCHEMES.
13. Aspects of Process Control.
V. CHARTS AND TABLES.
Collection of Tables and Charts.
Collection of Time Series Used for Examples in the Text and in Exercises.
VI. EXERCISES AND PROBLEMS.