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Inference in Constrained Quantile Regression Parker, Tom Feb 1, 2018

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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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48630-1.0369266.ris

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