Advertisement

A Heuristic Partial-Least-Squares Approach to Estimating Dynamic Path Models

  • Hans Gerhard Strohe
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

An approach to dynamic modelling with latent variables is proposed. It has been developed on the base of H. Wold’s Partial Least Squares (PLS). An operator matrix containing the lag operator L is substituted for the path coefficient matrix of Wold’s static PLS model. On what is called the dynamic PLS model (DPLS) the original PLS estimation algorithm is virtually applicable. Lagged and leaded latent variables are used in the iterative process of estimating the weights of the manifest variables. The path coefficients are estimated by OLS or an appropriate dynamic modelling method The redundancy coefficient allows to measure the forecasting validity. DPLS has been programmed in PC-ISP/DGS©. Some properties of DPLS will be shown by simulation.

Keywords

Partial Little Square Path Coefficient Path Model Partial Little Square Model Outer Model 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. GEPPERT, F. (1996): Bearbeitung, Programmierung, Simulation und Anwendung eines PLS-Algorithmus für einfache dynamische Modelle mit latenten Variablen. Diploma thesis supervised by H. G. Strohe, Universität Potsdam.Google Scholar
  2. JORESKOG, K.G. and SöRBOM, D. (1987): LISREL V II Program Manual. International Educational Services, Chicago.Google Scholar
  3. LOHMöLLER, J.-B. (1984): LVPLS 1.6 - Program Manual (Latent Variables Path Analysis with Partial Least Squares Estimation). Zentralarchiv für empirische Sozialforschung, Universität Köln.Google Scholar
  4. LOHMöLLER, J.-B. (1989): Latent Variable Path Modelling with Partial Least Squares. Heidelberg.Google Scholar
  5. MATHES, H. (1993): Der PLS-Ansatz für die Analyse von Pfadmodellen; Mathematical Systems in Economics. Anton Hain, Frankfurt/Main.Google Scholar
  6. PC-ISP (1992): Users Guide and Command Descriptions, Datavision AG, Schweiz.Google Scholar
  7. STROHE, H.G. (1993): Weiche Modellierung umweltökonomischer Zusammenhänge; in: Allgem. Statistisches Archiv 77, p. 281–310.Google Scholar
  8. STROHE, H.G. (1995): Dynamic Latent Variables Path Models - An Alternative PLS Estimation. Statistische Diskussionsbeiträge Nr. 1, Universität Potsdam.Google Scholar
  9. STROHE, H.G. and GEPPERT, F. (1997): DPLS - Algorithmus und Computerprogramm für dynamische Partial-Least-Squares-Modelle. Statistische Diskussionsbeiträge Nr. 7, Universität Potsdam.Google Scholar
  10. WOLD, H. (1973): Nonlinear Iterative Partial Least Squares (NIPALS) Modelling–Some Current Developement; in P.R. Krishnajah (Ed.), Multivariate Analysis (Vol. 3, p. 383–407 ), New York; Academic Press.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Hans Gerhard Strohe
    • 1
  1. 1.Lehrstuhl für StatistikUniversität PotsdamGermany

Personalised recommendations