All admissible linear estimators of a regression coefficient under a balanced loss function
Admissibility of linear estimators of a regression coefficient in linear models with and without the assumption that the underlying distribution is normal is discussed under a balanced loss function. In the non-normal case, a necessary and sufficient condition is given for linear estimators to be admissible in the space of homogeneous linear estimators. In the normal case, a sufficient condition is provided for restricted linear estimators to be admissible in the space of all estimators having finite risks under the balanced loss function. Furthermore, the sufficient condition is proved to be necessary in the normal case if additional conditions are assumed.
Year of publication: |
2011
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Authors: | Hu, Guikai ; Peng, Ping |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 102.2011, 8, p. 1217-1224
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Publisher: |
Elsevier |
Keywords: | Admissibility Space of all estimators With and without normality assumption Balanced loss function |
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