A new class of Bayes minimax estimators of the normal mean matrix for the case of common unknown variances

Zinodiny, S.; Rezaei, Satar; Arjmand, Omid Naghshineh; Nadarajah, Saralees

doi:10.1080/02331888.2017.1298598

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2024

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“…Ref. [18] obtained Bayes minimax estimators of the normal mean matrix for the case of common unknown variances.…”

Section: Introductionmentioning

confidence: 99%

A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution

Zinodiny,

Nadarajah

2024

Mathematics

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Bayes minimax estimation is important because it provides a robust approach to statistical estimation that considers the worst-case scenario while incorporating prior knowledge. In this paper, Bayes minimax estimation of the mean matrix of a matrix variate normal distribution is considered under the quadratic loss function. A large class of (proper and generalized) Bayes minimax estimators of the mean matrix is presented. Two examples are given to illustrate the class of estimators, showing, among other things, that the class includes classes of estimators presented by Tsukuma.

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“…Ref. [18] obtained Bayes minimax estimators of the normal mean matrix for the case of common unknown variances.…”

Section: Introductionmentioning

confidence: 99%

A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution

Zinodiny,

Nadarajah

2024

Mathematics

View full text Add to dashboard Cite

show abstract

A new class of Bayes minimax estimators of the normal mean matrix for the case of common unknown variances

Cited by 1 publication

References 13 publications

A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution

A New Class of Bayes Minimax Estimators of the Mean Matrix of a Matrix Variate Normal Distribution

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