Characterization of admissible linear estimators under extended balanced loss function

Title:

Characterization of admissible linear estimators under extended balanced loss function

Creator:

Mirezi, Buatikan and Kaçıranlar, Selahattin

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:ffd23a33-79a2-4caf-904d-97fdd4dbdf19
uuid:ffd23a33-79a2-4caf-904d-97fdd4dbdf19
doi:10.14736/kyb-2021-4-0613

Subject:

admissibility, extended balanced loss function, and linear admissible estimator

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

613-627

Source:

Kybernetika | 2021 Volume:57 | Number:4

Harvested from:

CDK

Metadata only:

false