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On the posterior distribution of the covariance matrix of the growth curve model

Author

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  • Pan, Jian-Xin
  • Fang, Kai-Tai
  • von Rosen, Dietrich

Abstract

For the growth curve model with an unstructured covariance matrix, the posterior distributions of the dispersion matrix is derived under a non-informative prior distribution. The results are especially useful for Bayesian inference as well as Bayesian diagnostics of the model.

Suggested Citation

  • Pan, Jian-Xin & Fang, Kai-Tai & von Rosen, Dietrich, 1998. "On the posterior distribution of the covariance matrix of the growth curve model," Statistics & Probability Letters, Elsevier, vol. 38(1), pages 33-39, May.
    • Handle: RePEc:eee:stapro:v:38:y:1998:i:1:p:33-39
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    References listed on IDEAS

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    1. von Rosen, Dietrich, 1989. "Maximum likelihood estimators in multivariate linear normal models," Journal of Multivariate Analysis, Elsevier, vol. 31(2), pages 187-200, November.
    2. Pan, Jian-Xin & Fang, Kai-Tai & Liski, Erkki P., 1996. "Bayesian Local Influence for the Growth Curve Model with Rao's Simple Covariance Structure," Journal of Multivariate Analysis, Elsevier, vol. 58(1), pages 55-81, July.
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    Cited by:

    1. Jian-Xin Pan & Wing-Kam Fung, 2000. "Bayesian Influence Assessment in the Growth Curve Model with Unstructured Covariance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(4), pages 737-752, December.

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