References
- Zellner A, Bayesian and non-Bayesian estimation using balanced loss functions. In: Gupta SS, Berger JO, editors. Statistical decision theory and related topics V. New York: Springer; 1994. p. 377–390.
- Xu XZ, Wu QG. Linear admissible estimators of regression coefficient under balanced loss. Acta Math Sci. 2000;20(4):468–473 (in Chinese).
- Hu GK, Peng P. Admissibility for linear estimators of regression coefficient in a general Gauss–Markoff model under balanced loss function. J Statist Plann Inference. 2010;140:3365–3375. doi: 10.1016/j.jspi.2010.05.004
- Hu GK, Peng P. All admissible linear estimators of a regression coefficient under a balanced loss function. J Multivariate Anal. 2011;102:1217–1224. doi: 10.1016/j.jmva.2011.04.003
- Cao MX. Φ-admissibility for linear estimators on regression coefficients in a general multivariate linear model under balanced loss function. J Statist Plann Inference. 2009;139:3354–3360. doi: 10.1016/j.jspi.2009.03.013
- Cao MX, Xu XZ, He DJ. Linearly admissible estimators of stochastic regression coefficient under balanced loss function. Statistics. 2014;48(2):359–366. doi: 10.1080/02331888.2013.766794
- Hu GK, Peng P. Matrix linear minimax estimators in a general multivariate linear model under a balanced loss function. J Multivariate Anal. 2012;111:286–295. doi: 10.1016/j.jmva.2012.04.004
- Hu GK, Ling QG, Peng P. Minimax estimator of regression coefficient in normal distribution under balanced loss function. Linear Algebra Appl. 2012;436:1228–1237. doi: 10.1016/j.laa.2011.08.013
- James W, Stein C. Estimation of quadratic loss. In: Proceedings of the Fourth Berkeley symposium on mathematical statistical probability. Vol. 1. Berkeley: University of California Press; 1961. p. 361–379.