Abstract

1. Introduction and Summary. 2. The Regression Model and Its Application in Forecasting. 3. Regression and Exponential Smoothing Methods to Forecast Nonseasonal Time Series. 4. Regression and Exponential Smoothing Methods to Forecast Seasonal Time Series. 5. Stochastic Time Series Models. 6. Seasonal Autoregressive Integrated Moving Average Models. 7. Relationships Between Forecasts from General Exponential Smoothing and Forecasts from Arima Time Series Models. 8. Special Topics. References. Exercises. Data Appendix. Table Appendix. Author Index. Subject Index.

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