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A geometric approach of the generalized least-squares estimation in analysis of covariance structures

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  • Wang, S. J.
  • Lee, Sik-Yum

Abstract

In this paper, the generalized least-squares estimation of the covariance structure model is studied from a geometrical point of view. General definitions of the intrinsic curvature and the parameter-effect curvature are defined for the model. Based on the general result, the second-order approximations of the bias and the covariance matrix of the generalized least-squares estimator are established. The information loss of the estimator is also computed under the multivariate normal assumption.

Suggested Citation

  • Wang, S. J. & Lee, Sik-Yum, 1995. "A geometric approach of the generalized least-squares estimation in analysis of covariance structures," Statistics & Probability Letters, Elsevier, vol. 24(1), pages 39-47, July.
    • Handle: RePEc:eee:stapro:v:24:y:1995:i:1:p:39-47
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    References listed on IDEAS

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    1. P. Bentler, 1983. "Some contributions to efficient statistics in structural models: Specification and estimation of moment structures," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 493-517, December.
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    Cited by:

    1. Shu-Jia Wang & Sik-Yum Lee, 1996. "Sensitivity analysis of structural equation models with equality functional constraints," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 239-256, December.

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