Skip Navigation

Biometrika 2001 88(3):859-864; doi:10.1093/biomet/88.3.859
© 2001 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Komaki, F.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Miscellaneous

A shrinkage predictive distribution for multivariate Normal observables

Fumiyasu Komaki1

1 Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japankomaki{at}stat.t.u-tokyo.ac.jp

We investigate shrinkage methods for constructing predictive distributions.We consider the multivariate Normal model with a known covariance matrix and show that there exists a shrinkage predictive distribution dominating the Bayesian predictive distribution based on the vague prior when the dimension is not less than three. Kullback–Leibler divergence from the true distribution to a predictive distribution is adopted as a loss function.

Key Words: Invariance; James–Stein estimator; Kullback–Leibler divergence; Stein's prior; Vague prior

Received August 2000. Revised December 2000


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.