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Admissibility in general Gauss–Markov model with respect to an ellipsoidal constraint under weighted balanced loss

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  • Gang Liu
  • Hong Yin

Abstract

Under weighted balanced loss function, we obtain the best linear unbiased estimator of regression coefficient in general Gauss–Markov model and discuss the admissibility of linear estimators of the regression coefficient with respect to an ellipsoidal constraint. We establish necessary and sufficient conditions for the admissibility of the linear estimators Ay(Ay+a) among the class of homogeneous and inhomogeneous linear estimators, respectively.

Suggested Citation

  • Gang Liu & Hong Yin, 2022. "Admissibility in general Gauss–Markov model with respect to an ellipsoidal constraint under weighted balanced loss," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(4), pages 1054-1066, February.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:4:p:1054-1066
    DOI: 10.1080/03610926.2020.1758140
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