Linearly admissible estimators on linear functions of regression coefficient under balanced loss function

MingXiang Cao and DaoJiang He

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 11, 2700-2706

Abstract: Linearly admissible estimators on linear functions of regression coefficient are studied in a singular linear model and balanced loss when the design matrix has not full column rank. The sufficient and necessary conditions for linear estimators to be admissible are obtained respectively in homogeneous and inhomogeneous classes.

Date: 2019
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DOI: 10.1080/03610926.2018.1472788

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