Chapter 9. Time Series

  1. Carlo Vercellis

Published Online: 17 MAR 2009

DOI: 10.1002/9780470753866.ch9

Business Intelligence: Data Mining and Optimization for Decision Making

Business Intelligence: Data Mining and Optimization for Decision Making

How to Cite

Vercellis, C. (2009) Time Series, in Business Intelligence: Data Mining and Optimization for Decision Making, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470753866.ch9

Author Information

  1. Politecnico di Milano, Italy

Publication History

  1. Published Online: 17 MAR 2009
  2. Published Print: 20 MAR 2009

ISBN Information

Print ISBN: 9780470511381

Online ISBN: 9780470753866

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Keywords:

  • aim of models for time series analysis;
  • basic concepts relating to time series;
  • evaluating time series models;
  • percentage prediction error;
  • distortion indices and mean errors (ME);
  • distortion and dispersion for errors density of three predictive models;
  • time series - trend, seasonality and random noise;
  • exponential smoothing with trend adjustment;
  • simple adaptive exponential smoothing

Summary

This chapter contains sections titled:

  • Definition of time series

  • Evaluating time series models

  • Analysis of the components of time series

  • Exponential smoothing models

  • Autoregressive models

  • Combination of predictive models

  • The forecasting process

  • Notes and readings