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Title	Inference in Constrained Quantile Regression
Creator	Parker, Tom
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2018-02-01T09:49
Description	I investigate the asymptotic distribution of linear quantile regression coefficient estimates when the parameter may lie on the boundary of the parameter space, and related inference procedures when the null hypothesis asserts that the parameters lie on a boundary of this set. Particular attention is paid to parameter spaces defined by sets of linear inequalities. I provide a uniform characterization of the constrained quantile regression process over an interval of quantile levels. This asymptotic theory is used to derive asymptotic inference methods for three related processes based on the constrained quantile regression process.
Extent	33 minutes
Subject	Mathematics Statistics Operations research, mathematical programming
Geographic Location	Banff (Alta.)
Type	Moving Image
FileFormat	video/mp4
Language	eng
Notes	Author affiliation: University of Waterloo
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2018-08-01
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0369266
URI	http://hdl.handle.net/2429/66633
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Researcher
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
AggregatedSourceRepository	DSpace

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