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Permanent link (DOI): https://doi.org/10.7939/R3416T718

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Variable Screening Based on Combining Quantile Regression Open Access

Descriptions

Other title
Subject/Keyword
quantile regression
average quantile regression
variable screening
composite quantile regression
B-spline approximations
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Shi, Qian
Supervisor and department
Kong, Linglong (Mathematical and Statistical Sciences)
Examining committee member and department
Cribben, Ivor (Business)
Mizera, Ivan (Mathematical and Statistical Sciences)
Prasad, Narasimha (Mathematical and Statistical Sciences)
Department
Department of Mathematical and Statistical Sciences
Specialization
Statistics
Date accepted
2014-08-22T15:50:33Z
Graduation date
2014-11
Degree
Master of Science
Degree level
Master's
Abstract
This thesis develops an efficient quantile-adaptive framework for linear and nonlinear variable screening with high-dimensional heterogeneous data. Inspired by the success of various variable screening methods, especially in the quantile-adaptive framework, we develop a more efficient variable screening procedure. Both the classical linear regression model and the nonlinear regression model are investigated. In the thesis, the information over different quantile levels are combined, which can be implemented in two ways. The first one is the (weighted) average quantile estimator based on a (weighted) average of quantile regression estimators at single quantiles. The other one is the (weighted) composite quantile regression estimator based on a (weighted) quantile loss function. Simulation studies are conducted to investigate the fine performance of the finite sample. A real data example is also analyzed.
Language
English
DOI
doi:10.7939/R3416T718
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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