Geodesic
Characterization of admissible linear estimators under extended balanced loss function
Kybernetika, Tome 57 (2021) no. 4, pp. 613-627 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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In this paper, we study the admissibility of linear estimator of regression coefficient in linear model under the extended balanced loss function (EBLF). The sufficient and necessary condition for linear estimators to be admissible are obtained respectively in homogeneous and non-homogeneous classes. Furthermore, we show that admissible linear estimator under the EBLF is a convex combination of the admissible linear estimator under the sum of square residuals and quadratic loss function.
In this paper, we study the admissibility of linear estimator of regression coefficient in linear model under the extended balanced loss function (EBLF). The sufficient and necessary condition for linear estimators to be admissible are obtained respectively in homogeneous and non-homogeneous classes. Furthermore, we show that admissible linear estimator under the EBLF is a convex combination of the admissible linear estimator under the sum of square residuals and quadratic loss function.
DOI : 10.14736/kyb-2021-4-0613
Classification : 62C15, 62F10, 62J05
Keywords: admissibility; extended balanced loss function; linear admissible estimator 
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     title = {Characterization of admissible linear estimators under extended balanced loss function},
     journal = {Kybernetika},
     pages = {613--627},
     year = {2021},
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Mirezi, Buatikan; Kaçıranlar, Selahattin. Characterization of admissible linear estimators under extended balanced loss function. Kybernetika, Tome 57 (2021) no. 4, pp. 613-627. doi: 10.14736/kyb-2021-4-0613

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