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Dimension Reduction in Multivariate Time Series

  • Daniel Peña
  • Pilar Poncela
Chapter
Part of the Statistics for Industry and Technology book series (SIT)

Abstract

This chapter compares models for dimension reduction in time series and tests of the dimension of the dynamic structure. We consider both stationary and nonstationary time series and discuss principal components, canonical analysis, scalar component models, reduced rank models, and factor models. The unifying view of canonical correlation analysis between the present and past values of the series is emphasized. Then, we review some of the tests based on canonical correlation analysis to find the dimension of the dynamic relationship among the time series. Finally, the procedures are compared through a real data example.

Keywords and phrases

Canonical correlation analysis dimension reduction vector time series 

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Copyright information

© Birkhäuser Boston 2006

Authors and Affiliations

  • Daniel Peña
    • 1
    • 2
  • Pilar Poncela
    • 1
    • 2
  1. 1.Universidad Carlos III de MadridMadridSpain
  2. 2.Universidad Autónoma de MadridMadridSpain

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