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Estimation of Variance Components in Mixed Linear Models

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  • Kubokawa, T.

Abstract

In mixed linear models with two variance components, classes of estimators improving on ANOVA estimators for the variance components and the ratio of variances are constructed on the basis of the invariant statistics. Out of the classes, consistent, improved and positive estimators are singled out. These estimators are shown to be further dominated by utilizing the information contained in the noninvariant statistics. Applications to the unbalanced one-way ANOVA models and to balanced incomplete block designs are given.

Suggested Citation

  • Kubokawa, T., 1995. "Estimation of Variance Components in Mixed Linear Models," Journal of Multivariate Analysis, Elsevier, vol. 53(2), pages 210-236, May.
    • Handle: RePEc:eee:jmvana:v:53:y:1995:i:2:p:210-236
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    Cited by:

    1. Nicholas T. Longford, 2015. "On the inefficiency of the restricted maximum likelihood," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(2), pages 171-196, May.
    2. Bobotas, Panayiotis & Kourouklis, Stavros, 2017. "Estimation of the smallest normal variance with applications to variance components models," Statistics & Probability Letters, Elsevier, vol. 131(C), pages 38-45.
    3. Nicholas Longford, 2014. "On the inefficiency of the restricted maximum likelihood," Economics Working Papers 1415, Department of Economics and Business, Universitat Pompeu Fabra.

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