TY - JOUR
AU - Zinodiny, Shokofeh
AU - Rezaei, Sadegh
AU - Nadarajah, Saralees
PY - 2017/01/01
Y2 - 2024/08/13
TI - Minimax Estimation of the Mean Matrix of the Matrix Variate Normal Distribution under the Divergence Loss Function
JF - Statistica
JA - Stat
VL - 77
IS - 4
SE - Articles
DO - 10.6092/issn.1973-2201/6956
UR - https://rivista-statistica.unibo.it/article/view/6956
SP - 369-384
AB - <p>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.</p>
ER -