1.Cao Mingxiang *, Sun Peng, He Daojiang, Wang Rui, Xu Xingzhong. A test on linear hypothesis of k-sample means in high-dimensional data, Statistics and Its Interface, 2020(13): 27-36. (SCI)2.Cao Mingxiang, Park Junyong*, He Daojiang. A test for the k sample Behrens-Fisher problem in high dimensional data. Journal of Statistical Planning and Inference, 2019, 201: 86–102. (SCI)3.Cao Mingxiang*, He Daojiang. Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function. Journal of Multivariate Analysis, 2017, 153: 246–254. (SCI)4.Cao Mingxiang*. Admissibility of linear estimators for the stochastic regression coefficient in a general Gauss-Markoff model under a balanced loss function. Journal of Multivariate Analysis, 2014(124): 25—30. (SCI)5.Cao Mingxiang*. Φ admissibility of stochastic regression coefficients in a general multivariate random effects model under a generalized balanced loss function. Electronic Journal of Statistics, 2012(6): 2332—2346. (SCI)6.Cao Mingxiang*.Φ admissibility for linear estimators on regression coefficients in a general multivariate linear model under balanced loss function. Journal of Statistical Planning and Inference, 2009(9): 3354 —3360. (SCI)
