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Estimating a reduced rank regression model for non‐normal variables

Author

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  • Catrien C. J. H. Bijleveld
  • Kees Van Montfort

Abstract

A method using third order moments for estimating the regression coefficients as well as the latent state scores of the reduced‐rank regression model when the latent variable(s) are non‐normally distributed is presented in this paper. It is shown that the factor analysis type indeterminacy of the regression coefficient matrices is eliminated. A real life example of the proposed method is presented. Differences of this solution with the reduced‐rank regression eigen solution are discussed.

Suggested Citation

  • Catrien C. J. H. Bijleveld & Kees Van Montfort, 1991. "Estimating a reduced rank regression model for non‐normal variables," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 7(3), pages 281-289, September.
    • Handle: RePEc:wly:apsmda:v:7:y:1991:i:3:p:281-289
    DOI: 10.1002/asm.3150070307
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