Harmonic Bayesian Prediction Under α -Divergence

• Maruyama, Yuzo

• Matsuda, Takeru

• Ohnishi, Toshio

Bibliographic Information

Other Title

• Harmonic Bayesian Prediction Under $\alpha$ -Divergence

Abstract

We investigate Bayesian shrinkage methods for constructing predictive distributions. We consider the multivariate normal model with a known covariance matrix and show that the Bayesian predictive density with respect to Stein's harmonic prior dominates the best invariant Bayesian predictive density when the dimension is greater than or equal to 3. Alpha divergence from the true distribution to a predictive distribution is adopted as a loss function.

Journal

• IEEE Transactions on Information Theory

  IEEE Transactions on Information Theory 65 (9), 5352-5366, 2019-05-07

  IEEE

Keywords

• Bayesian predictive density
• harmonic prior
• minimaxity

Details

• CRID: 1050294045368674560
• NII Article ID: 120007017124
• DOI: 10.1109/tit.2019.2915245
• ISSN: 15579654
• ISSN: 00189448
• HANDLE: 20.500.14094/90008138
• Web Site: http://xplorestaging.ieee.org/ielx7/18/8804391/08708681.pdf?arnumber=8708681
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN