Autori: Nadarajah, Saralees , Zinodiny, Shokofeh , Rezaei, Sadegh
Titolo: Minimax Estimation of the Mean Matrix of the Matrix Variate Normal Distribution under the Divergence Loss Function
Periodico: Statistica
Anno: 2017 - Volume: 77 - Fascicolo: 4 - Pagina iniziale: 369 - Pagina finale: 384

Abstract Traduci Abstract The problem of estimating the mean matrix of a matrix-variate normal distribution with a covariance matrix is considered under two loss functions. We construct a class of empirical Bayes estimators which are better than the maximum likelihood estimator under the first loss function and hence show that the maximum likelihood estimator is inadmissible. We find a general class of minimax estimators. Also we give a class of estimators that improve on the maximum likelihood estimator under the second loss function and hence show that the maximum likelihood estimator is inadmissible.


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SICI: 0390-590X(2017)77:4<369:MEOTMM>2.0.ZU;2-B

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