| GAMMA－MINIMAX ESTIMATORS FOR THE MEAN OF A MULTIVARIATE NORMAL DISTRIBUTION WITH PARTIALLY UNKNOWN COVARIANCE MATRIX |
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| 引用本文： | 陈兰祥.GAMMA－MINIMAX ESTIMATORS FOR THE MEAN OF A MULTIVARIATE NORMAL DISTRIBUTION WITH PARTIALLY UNKNOWN COVARIANCE MATRIX[J].应用数学学报(英文版),1995,11(1):11-16. |
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| 作者姓名： | 陈兰祥 |
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| 作者单位： | CHEN LANXING (Department of Mathematics,Tongji University,Shanghai 200092,China)JURGEN LEHN (Fachbereich Mathematik Technische Hochschule,Darmstadt,Germany) |
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| 摘 要： | ＧＡＭＭＡ－ＭＩＮＩＭＡＸＥＳＴＩＭＡＴＯＲＳＦＯＲＴＨＥＭＥＡＮＯＦＡＭＵＬＴＩＶＡＲＩＡＴＥＮＯＲＭＡＬＤＩＳＴＲＩＢＵＴＩＯＮＷＩＴＨＰＡＲＴＩＡＬＬＹＵＮＫＮＯＷＮＣＯＶＡＲＩＡＮＣＥＭＡＴＲＩＸＣＨＥＮＬＡＮＸＩＮＧ（陈兰祥）（Ｄｅｐａｒｔ...
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| 收稿时间： | 18 March 1991 |
Gamma-minimax estimators for the mean of a multivariate normal distribution with partially unknown covariance matrix |
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| Lanxing Chen,Jürgen Lehn.Gamma-minimax estimators for the mean of a multivariate normal distribution with partially unknown covariance matrix[J].Acta Mathematicae Applicatae Sinica,1995,11(1):11-16. |
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| Authors: | Lanxing Chen Jürgen Lehn |
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| Institution: | (1) Department of Mathematics, Tongji University, 200092 Shanghai, China;(2) Fachbereich Mathematik Technische Hochschule, Darmstadt, Germany |
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| Abstract: | In this paper  -minimax estimation of a multivariate normal mean under arbitrary squared error loss is considered where the covariance matrix of the normal distribution is a known symmetric and positive definite matrix with unknown multiple. The set is fixed by imposing restrictions on the vector of first moments and on the matrix of second moments as well as on the first moment of the unknown factor determining of the covariance matrix. Necessary and sufficient conditions are derived which ensure that an estimator is -minimax and that a prior is least favorable in . |
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| Keywords: | Bayes estimation minimax estimation |
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