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The best linear unbiased estimator in a singular linear regression model

Author

Listed:
  • Jibo Wu

    (Chongqing University of Arts and Sciences)

  • Chaolin Liu

    (Chongqing University)

Abstract

In this paper, the best linear unbiased estimator of regression coefficients in the singular linear model was considered. Under the weighted balanced loss function the minimum risk properties of linear estimators of regression coefficients in the class of linear unbiased estimators are derived. Some kinds of relative efficiencies of the best linear unbiased estimator are given, and the lower bounds or upper bounds of these relative efficiencies are also presented.

Suggested Citation

  • Jibo Wu & Chaolin Liu, 2018. "The best linear unbiased estimator in a singular linear regression model," Statistical Papers, Springer, vol. 59(3), pages 1193-1204, September.
    • Handle: RePEc:spr:stpapr:v:59:y:2018:i:3:d:10.1007_s00362-016-0811-6
    DOI: 10.1007/s00362-016-0811-6
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    References listed on IDEAS

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    1. Litong Wang & Hu Yang, 2012. "Matrix Euclidean norm Wielandt inequalities and their applications to statistics," Statistical Papers, Springer, vol. 53(3), pages 521-530, August.
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