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| Preface | |
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| Acknowledgments | |
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| Overview of Time Series | |
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| Introduction | |
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| Analysis Methods and SAS/ETS Software | |
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| Options | |
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| How SAS/ETS Software Procedures Interrelate | |
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| Simple Models: Regression | |
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| Linear Regression | |
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| Highly Regular Seasonality | |
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| Regression with Transformed Data | |
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| Simple Models: Autoregression | |
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| Introduction | |
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| Terminology and Notation | |
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| Statistical Background | |
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| Forecasting | |
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| Forecasting with PROC ARIMA | |
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| Backshift Notation B for Time Series | |
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| Yule-Walker Equations for Covariances | |
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| Fitting an AR Model in PROC REG | |
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| The General ARIMA Model | |
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| Introduction | |
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| Statistical Background | |
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| Terminology and Notation | |
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| Prediction | |
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| One-Step-Ahead Predictions | |
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| Future Predictions | |
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| Model Identification | |
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| Stationarity and Invertibility | |
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| Time Series Identification | |
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| Chi-Square Check of Residuals | |
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| Summary of Model Identification | |
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| Examples and Instructions | |
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| IDENTIFY Statement for Series 1-8 | |
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| Example: Iron and Steel Export Analysis | |
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| Estimation Methods Used in PROC ARIMA | |
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| ESTIMATE Statement for Series 8 | |
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| Nonstationary Series | |
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| Effect of Differencing on Forecasts | |
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| Examples: Forecasting IBM Series and Silver Series | |
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| Models for Nonstationary Data | |
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| Differencing to Remove a Linear Trend | |
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| Other Identification Techniques | |
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| Summary | |
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| The ARIMA Model: Introductory Applications | |
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| Seasonal Time Series | |
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| Introduction to Seasonal Modeling | |
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| Model Identification | |
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| Models with Explanatory Variables | |
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| Case 1: Regression with Time Series Errors | |
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| Case 1A: Intervention | |
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| Case 2: Simple Transfer Function | |
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| Case 3: General Transfer Function | |
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| Case 3A: Leading Indicators | |
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| Case 3B: Intervention | |
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| Methodology and Example | |
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| Case 1: Regression with Time Series Errors | |
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| Case 2: Simple Transfer Functions | |
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| Case 3: General Transfer Functions | |
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| Case 3B: Intervention | |
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| Further Examples | |
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| North Carolina Retail Sales | |
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| Construction Series Revisited | |
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| Milk Scare (Intervention) | |
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| Terrorist Attack | |
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| The ARIMA Model: Special Applications | |
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| Regression with Time Series Errors and Unequal Variances | |
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| Autoregressive Errors | |
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| Example: Energy Demand at a University | |
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| Unequal Variances | |
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| ARCH, GARCH, and IGARCH for Unequal Variances | |
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| Cointegration | |
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| Introduction | |
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| Cointegration and Eigenvalues | |
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| Impulse Response Function | |
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| Roots in Higher-Order Models | |
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| Cointegration and Unit Roots | |
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| An Illustrative Example | |
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| Estimating the Cointegrating Vector | |
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| Intercepts and More Lags | |
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| PROC VARMAX | |
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| Interpreting the Estimates | |
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| Diagnostics and Forecasts | |
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| State Space Modeling | |
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| Introduction | |
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| Some Simple Univariate Examples | |
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| A Simple Multivariate Example | |
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| Equivalence of State Space and Vector ARMA Models | |
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| More Examples | |
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| Some Univariate Examples | |
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| ARMA(1,1) of Dimension 2 | |
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| PROC STATESPACE | |
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| State Vectors Determined from Covariances | |
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| Canonical Correlations | |
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| Simulated Example | |
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| Spectral Analysis | |
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| Periodic Data: Introduction | |
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| Example: Plant Enzyme Activity | |
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| PROC SPECTRA Introduced | |
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| Testing for White Noise | |
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| Harmonic Frequencies | |
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| Extremely Fast Fluctuations and Aliasing | |
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| The Spectral Density | |
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| Some Mathematical Detail (Optional Reading) | |
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| Estimating the Spectrum: The Smoothed Periodogram | |
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| Cross-Spectral Analysis | |
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| Interpreting Cross-Spectral Quantities | |
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| Interpreting Cross-Amplitude and Phase Spectra | |
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| PROC SPECTRA Statements | |
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| Cross-Spectral Analysis of the Neuse River Data | |
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| Details on Gain, Phase, and Pure Delay | |
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| Data Mining and Forecasting | |
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| Introduction | |
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| Forecasting Data Model | |
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| The Time Series Forecasting System | |
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| HPF Procedure | |
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| Scorecard Development | |
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| Business Goal Performance Metrics | |
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| Graphical Displays | |
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| Goal-Seeking Model Development | |
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| Summary | |
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| References | |
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| Index | |