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Estimation of the Cholesky decomposition of the covariance matrix for a conditional independent normal model

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  • Sun, Xiaoqian
  • Sun, Dongchu

Abstract

In this paper, we consider estimating the Cholesky decomposition (the lower triangular squared root) of the covariance matrix for a conditional independent normal model under four equivariant loss functions. Closed-form expressions of the maximum likelihood estimator and an unbiased estimator of the Cholesky decomposition are provided. By introducing a special group of lower-triangular block matrices, we obtain the best equivariant estimator of the Cholesky decomposition under each of the four losses. Because both the maximum likelihood estimator and the unbiased estimator belong to the class of equivariant estimators with respect to the special group, they are all inadmissible.

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  • Sun, Xiaoqian & Sun, Dongchu, 2005. "Estimation of the Cholesky decomposition of the covariance matrix for a conditional independent normal model," Statistics & Probability Letters, Elsevier, vol. 73(1), pages 1-12, June.
    • Handle: RePEc:eee:stapro:v:73:y:2005:i:1:p:1-12
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    References listed on IDEAS

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    1. Ghosh M. & Sinha B. K., 1987. "Inadmissibility Of The Best Equivariant Estimators Of The Variance-Covariance Matrix, The Precision Matrix, And The Generalized Variance Under Entropy Loss," Statistics & Risk Modeling, De Gruyter, vol. 5(3-4), pages 201-228, April.
    2. Konno, Yoshihiko, 2001. "Inadmissibility of the Maximum Likekihood Estimator of Normal Covariance Matrices with the Lattice Conditional Independence," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 33-51, October.
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    Cited by:

    1. He, Daojiang & Xu, Kai, 2014. "Estimation of the Cholesky decomposition in a conditional independent normal model with missing data," Statistics & Probability Letters, Elsevier, vol. 88(C), pages 27-39.
    2. Minjeong Jeon & Frank Rijmen & Sophia Rabe-Hesketh, 2013. "Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model," Journal of Educational and Behavioral Statistics, , vol. 38(1), pages 32-60, February.

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