Title	Ensemble minimaxity of James-Stein estimators
Creator	Maruyama, Yuzo
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2019-04-11T15:42
Description	We consider estimation of a heteroscedastic multivariate normal mean. Under heteroscedasticity, estimators shrinking more on the coordinates with larger variances, seem desirable. However, they are not necessarily ordinary minimax. We show that such James-Stein type estimators can be ensemble minimax, minimax with respect to the ensemble risk, related to empirical Bayes perspective of Efron and Morris. This is a joint work with Larry Brown and Ed George.
Extent	48.0 minutes
Subject	Mathematics; Statistics
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of Tokyo
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2019-10-09
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0383330
URI	http://hdl.handle.net/2429/71871
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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