Title	Active set methods for log-concave densities and nonparametric tail inflation
Creator	Duembgen, Lutz
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2018-01-31T11:00
Description	In this talk we discuss nonparametric estimation of a log-concave density and nonparametric estimation of a tail inflation function (McCullagh and Polson, 2012) in a common framework. A variation of the latter model assumes data coming from a density $f_0(x) \exp(\rho(x))$ with a given density $f_0$ and $\rho$ being an unknown convex function, a so-called tail inflation function. We discuss and illustrate a variation of the active set approach by Duembgen, Huesler and Rufibach (2007/2011) which works in both settings. This is joint work with Peter McCullagh, Alexandre Moesching and Christof Straehl.
Extent	42 minutes
Subject	Mathematics; Statistics; Operations research, mathematical programming
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of Bern
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2018-07-31
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0369259
URI	http://hdl.handle.net/2429/66626
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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