Mathematics
a year ago

New priors revolutionize normal mean matrix estimation, outperforming maximum likelihood.

arXiv (Cornell University)
Double shrinkage priors for a normal mean matrix
Takeru Matsuda, Fumiyasu Komaki, William E. Strawderman

Paper Summary

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The article explores ways to estimate a normal mean matrix more accurately. Researchers developed new priors that shrink values towards zero, improving estimation. These priors outperform traditional methods and reduce errors in predictions.