Partial Least Squares

Partial Least Squares
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Die Partial Least Squares (PLS) Pfadanalyse ist ein statistisches Verfahren zur Schätzung von Kausalmodellen. Sie gehört zur Familie der NILES (Nonlinear Iterative Least Squares) Methoden, die vor allem von Herman Wold 1966 entwickelt wurden[1]. Diese iterativen Verfahren bieten die Möglichkeit einer alternativen Schätzung verschiedener statistischer Methoden. Dazu zählen die Hauptkomponentenanalyse, die Kanonische Korrelationsanalyse, die Multiple Regression und die Faktorenanalyse.

Das PLS-Verfahren versucht, die tatsächlichen Fallwerte für ein Kausalmodell mit Hilfe einer Least-Squares-Schätzung genau zu prognostizieren.

Für die PLS-Pfadanalyse existieren verschiedene Software-Applikationen, zum Beispiel LVPLS (Latent Variable Partial Least Square), PLSGraph, SmartPLS, PLS-GUI oder SPAD-PLS[2].

Inhaltsverzeichnis

Literatur

  • Haenlein, M., Kaplan, A.M.: A beginner's guide to partial least squares (PLS) analysis. In: Understanding Statistics. 3, Nr. 4, 2004, S. 283-297, doi:10.1207/s15328031us0304_4.

Weblinks

Weiterführende Informationen

Software

Einzelnachweise

  1. ↑ Wold, H. (1966), Estimation of Principal Components and Related Models by Iterative Least Squares, in Multivariate Analysis, ed. P. R. Krishnaiah, New York: Academic Press, Seiten 391-420.
  2. ↑ Temme, D., Kreis, H., Hildebrandt, L. (2010): A Comparison of Current PLS Path Modeling Software: Features, Ease-of-Use, and Performance, in: V. E. Vinzi, W. W. Chin, J. Henseler, H. Wang (eds.): Handbook of Partial Least Squares - Concepts, Methods and Applications, Springer, Berlin

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