Forecasting and time series : an applied approach


Forecasting and time series : an applied approach

Bruce L. Bowerman, Richard T. O'Connell

(The Duxbury advanced series in statistics and decision sciences)

Duxbury Press, c1993

3rd ed

大学図書館所蔵 件 / 3



Rev. ed. of: Time series forecasting. 2nd ed. c1987

Includes bibliographical references (p. 716-718) and index



This text introduces readers to time series and forecasting techniques and contains coverage of linear regression analysis, which provides much of the conceptual foundation of forecasting. A chapter on basic statistical concepts and nearly 400 new computer printouts of Minitab and SAS have been added. Extensive use of Minitab and SAS output, including end-of-chapter sections explaining the use of these packages, gives students experience using forecasting software.


  • An introduction to forecasting
  • Basic statistical concepts
  • Forecasting by using regression analysis
  • Simple linear regression
  • Multiple regression
  • Topics in regression analysis
  • Forecasting by using time series regression, decomposition methods and exponential smoothing
  • Time series regression
  • Decomposition methods
  • Exponential smoothing
  • Forecasting by using basic techniques of the box Jenkins methodology
  • Nonseasonal, box-Jenkins models and their tentative identification
  • Estimation, diagnostic checking and forecasting for nonseasonal box-Jenkins models
  • An introduction to box-Jenkins seasonal modelling
  • Forecasting by using advanced technology of the box-Jenkins methodology
  • General box-Jenkins seasonal modelling
  • Using the box-Jenkins methodology to improve time series regression models and to implement exponential smoothing
  • Transfer functions and intervention models.

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