Description

Book Synopsis
This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. .

Table of Contents
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.

Statistical Methods for Forecasting

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    A Paperback / softback by Bovas Abraham, Johannes Ledolter

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      Book details

      Publisher John Wiley & Sons Inc
      Published 21 October 2005
      ISBN-13 9780471769873
      978-0471769873
      ISBN-10 0471769878
      Also in:
      Mathematics

      Description

      Book Synopsis
      This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. .

      Table of Contents
      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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