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A new procedure for the estimation of variance components

Author

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  • Chow, Shein-Chung
  • Shao, Jun

Abstract

For the estimation of variance components in the one way random effects models, we propose some estimators which avoid negative and zero estimates of the variance component, a well-known problem with customary estimators such as the maximum likelihood or the restricted maximum likelihood estimators. The proposed estimators are shown to have lower mean squared error than customary estimators over a large range of the parameter space. This is also exhibited in a Monte Carlo study. Extensions of the proposed procedure to more complex situations are also discussed.

Suggested Citation

  • Chow, Shein-Chung & Shao, Jun, 1988. "A new procedure for the estimation of variance components," Statistics & Probability Letters, Elsevier, vol. 6(5), pages 349-355, April.
    • Handle: RePEc:eee:stapro:v:6:y:1988:i:5:p:349-355
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    Cited by:

    1. Sutradhar, Brajendra C., 1997. "A multivariate approach for estimating the random effects variance component in one-way random effects model," Statistics & Probability Letters, Elsevier, vol. 33(4), pages 333-339, May.

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