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 ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback