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Experimental Design for Variable Selection in data bases

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  • Pumplün, Constanze
  • Weihs, Claus
  • Preusser, Andrea

Abstract

This paper analyses the influence of 13 stylized facts of the German economy on the West German business cycles from 1955 to 1994. The method used in this investigation is Statistical Experimental Design with orthogonal factors. We are looking for all existing Plackett-Burman designs realizable by coded observations of these data. The plans are then analysed by regression with forward selection and various classification methods to extract the relevant variables for separating upswing and downswing of the cycles. The results are compared with already existing studies on this topic.

Suggested Citation

  • Pumplün, Constanze & Weihs, Claus & Preusser, Andrea, 2004. "Experimental Design for Variable Selection in data bases," Technical Reports 2004,72, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200472
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    References listed on IDEAS

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    1. Weihs, Claus & Garczarek, Ursula, 2002. "Stability of multivariate representation of business cycles over time," Technical Reports 2002,20, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Weihs, Claus & Röhl, Michael C. & Theis, Winfried, 1999. "Multivariate classification of business phases," Technical Reports 1999,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Heilemann Ullrich & Münch Heinz Josef, 1999. "Classification of West German Business Cycles 1955-1994 / Klassifikation westdeutscher Konjunkturzyklen 1955 - 1994," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 219(5-6), pages 632-656, October.
    4. Heilemann, Ullrich & Münch, Heinz Josef, 1999. "Classification of west german business cycles," Technical Reports 1999,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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