Title	On the nonparametric maximum likelihood estimator for Gaussian location mixture densities and applications
Creator	Guntuboyina, Aditya
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2019-04-09T14:18
Description	I will start by presenting some Hellinger accuracy results for the Nonparametric Maximum Likelihood Estimator (NPMLE) for Gaussian location mixture densities. I will then present two applications of the NPMLE: (a) empirical Bayes estimation of multivariate normal means, and (b) a multiple hypothesis testing problem involving univariate normal means. I will also talk about an extension to the mixture of linear regressions model. This is based on joint work with several collaborators who will be mentioned during the talk.
Extent	40.0 minutes
Subject	Mathematics; Statistics
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of California, Berkeley
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2019-10-07
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0383296
URI	http://hdl.handle.net/2429/71837
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Researcher
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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