In this paper, the multivariate linear model Y = XB+e, e ~ Nm×k(0, ImΣ) is considered from the Bayes perspective. Under the normal-inverse Wishart prior for (BΣ), the Bayes estimators are derived. The sup...In this paper, the multivariate linear model Y = XB+e, e ~ Nm×k(0, ImΣ) is considered from the Bayes perspective. Under the normal-inverse Wishart prior for (BΣ), the Bayes estimators are derived. The superiority of the Bayes estimators of B and Σ over the least squares estimators under the criteria of Bayes mean squared error (BMSE) and Bayes mean squared error matrix (BMSEM) is shown. In addition, the Pitman Closeness (PC) criterion is also included to investigate the superiority of the Bayes estimator of B.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.11201005,11071015)the Foundation of National Bureau of Statistics(Grant No.2013LZ17)the Natural Science Foundation of Anhui Province(Grant No.1308085QA13)
文摘In this paper, the multivariate linear model Y = XB+e, e ~ Nm×k(0, ImΣ) is considered from the Bayes perspective. Under the normal-inverse Wishart prior for (BΣ), the Bayes estimators are derived. The superiority of the Bayes estimators of B and Σ over the least squares estimators under the criteria of Bayes mean squared error (BMSE) and Bayes mean squared error matrix (BMSEM) is shown. In addition, the Pitman Closeness (PC) criterion is also included to investigate the superiority of the Bayes estimator of B.