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Admissible minimax estimators for the shape parameter of Topp–Leone distribution

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  • Husam Awni Bayoud

Abstract

The shape parameter of Topp–Leone distribution is estimated in this article from the Bayesian viewpoint under the assumption of known scale parameter. Bayes and empirical Bayes estimates of the unknown parameter are proposed under non informative and suitable conjugate priors. These estimates are derived under the assumption of squared and linear-exponential error loss functions. The risk functions of the proposed estimates are derived in analytical forms. It is shown that the proposed estimates are minimax and admissible. The consistency of the proposed estimates under the squared error loss function is also proved. Numerical examples are provided.

Suggested Citation

  • Husam Awni Bayoud, 2016. "Admissible minimax estimators for the shape parameter of Topp–Leone distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(1), pages 71-82, January.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:1:p:71-82
    DOI: 10.1080/03610926.2013.818700
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    Cited by:

    1. Mustapha Muhammad & Lixia Liu & Badamasi Abba & Isyaku Muhammad & Mouna Bouchane & Hexin Zhang & Sani Musa, 2023. "A New Extension of the Topp–Leone-Family of Models with Applications to Real Data," Annals of Data Science, Springer, vol. 10(1), pages 225-250, February.

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