Many multivariate data-analysis techniques for an m × n matrix Y are related to the model Y = M + E, where Y is an m × n matrix of full rank and M is an unobserved mean matrix of rank K < (m Λ n).
We develop singular value shrinkage priors for the mean matrix parameters in the matrixvariate normal model with known covariance matrices. Our priors are superharmonic and put more weight on matrices ...
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