Linearly admissible estimators of mean vector with respect to balanced loss function in multivariate statistics

Ming-Xiang Cao and Guang-Jun Shena

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 4, 1063-1069

Abstract: Let X1, X2,…, Xn be random samples from a probability model with mean vector β and covariance matrix Σ where both β∈Rp$\beta \in \mathcal {R}^{p}$ and Σ > 0 are unknown. Zellner’s balanced loss function is adopted to estimate β. Sufficient and necessary conditions for linear estimators to be admissible in classes of homogeneous and non homogeneous linear estimators are obtained, respectively, which extend the results of Xu (1996).

Date: 2016
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DOI: 10.1080/03610926.2013.854912

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