9. Additional Topics

  1. Søren Bisgaard and
  2. Murat Kulahci

Published Online: 31 MAY 2011

DOI: 10.1002/9781118056943.ch9

Time Series Analysis and Forecasting by Example

Time Series Analysis and Forecasting by Example

How to Cite

Bisgaard, S. and Kulahci, M. (2011) Additional Topics, in Time Series Analysis and Forecasting by Example, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118056943.ch9

Author Information

  1. Technical University of Denmark

Publication History

  1. Published Online: 31 MAY 2011
  2. Published Print: 5 JUL 2011

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470540640

Online ISBN: 9781118056943

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Keywords:

  • autocorrelation;
  • canonical analysis;
  • multiple time series;
  • principal component analysis (PCA);
  • spurious regression;
  • structural analysis

Summary

This chapter demonstrates the problem of spurious regression for autocorrelated data using a simulated example. It discusses the issue of autocorrelation in regression analysis in general. The chapter also discusses a notorious example from economics to show how regression analysis can be seriously misleading if the assumption of independence of the errors is violated. The kind of graphical analysis also demonstrated in the chapter is useful in the early diagnostic phase of analyzing processes suspected of having undergone regime changes. The chapter describes two different approaches such as principal component analysis (PCA) and canonical analysis of multiple time series offering different structural analysis of the data.

Controlled Vocabulary Terms

autocorrelation; Canonical analysis; canonical correlation; principal components analysis; time series