题　目：Shrinkage Estimators for the Mean Matrix of a Multivariate Complex Normal Distribution 主讲人： Prof. Yoshihiko Konno(今野良彦) (Japan Women’s University, Japan) 时　间：101年12月5日(星期三)下午13:30-14:20 地　点：交大综合一馆427室 Abstract Lillestøl (1977) investigated Stein-like shrinkage estimators for the mean vector of a complex normal model. However, the shrinkage methods for this model have received less attention so far, although it is important to develop these methods beyond the maximum likelihood estimator of the unknown signals in the multivariate complex normal distribution. The goal of this talk is to show how certain decision theoretical results concerning the problem of estimating a mean matrix of the real normal distribution can be extended to the complex multivariate normal case. The problem of estimating a mean matrix of a multivariate complex normal distribution with an unknown covariance matrix is considered under an invariant loss function. By using complex versions of the Stein identity and the Stein-Haidentity, a formula is obtained for an unbiased estimate of the risk of an invariant class of estimators, from which several minimax shrinkage estimators are constructed. --

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