Estimating a reduced rank regression model for non‐normal variables

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

Applied Stochastic Models and Data Analysis, 1991, vol. 7, issue 3, 281-289

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.

Date: 1991
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https://doi.org/10.1002/asm.3150070307

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmda:v:7:y:1991:i:3:p:281-289

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