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Brief History of Seasonal Adjustment

  • Dominique Ladiray
  • Benoît Quenneville
Part of the Lecture Notes in Statistics book series (LNS, volume 158)

Abstract

It is common today to decompose an observed time series X t into several components, themselves unobserved, according to a model such as:
$$ X_t = T_t + C_t + S_t + I_t , $$
where T t ,C t ,S t and I t designate, respectively, the trend, the cycle, the seasonality and the irregular components. This is an old idea, and it is doubtless to astronomy that one should turn to find its origin1.

Keywords

Local Regression ARIMA Model Observe Time Series Calendar Effect Seasonal Adjustment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Dominique Ladiray
    • 1
  • Benoît Quenneville
    • 2
  1. 1.EUROSTAT, BECH E4/813Bâtiment Jean MonnetLuxemborgBelgium
  2. 2.Statistics CanadaOttawaCanada

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