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Asymptotic equivalence of unique variance estimators in marginal and conditional factor analysis models

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  • Ihara, Masamori
  • Kano, Yutaka

Abstract

It is shown that the maximum likelihood and generalized least-squares estimators of unique variances in the conditional model are asymptotically equivalent to those in the marginal model in factor analysis. The asymptotic covariance matrices of the estimators are expressed in matrix form.

Suggested Citation

  • Ihara, Masamori & Kano, Yutaka, 1992. "Asymptotic equivalence of unique variance estimators in marginal and conditional factor analysis models," Statistics & Probability Letters, Elsevier, vol. 14(5), pages 337-341, July.
    • Handle: RePEc:eee:stapro:v:14:y:1992:i:5:p:337-341
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    Cited by:

    1. Hayashi, Kentaro & Kumar Sen, Pranab, 1998. "On Covariance Estimators of Factor Loadings in Factor Analysis," Journal of Multivariate Analysis, Elsevier, vol. 66(1), pages 38-45, July.

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