Multiscale Exploratory Analysis of Regression Quantiles Using Quantile SiZer

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The SiZer methodology proposed by Chaudhuri and Marron (1999) is a valuable tool for conducting exploratory data analysis. Since its inception different versions of SiZer have been proposed in the literature. Most of these SiZer variants are targeting the mean structure of the data, and are incapable of providing any information about the quantile composition of the data. To till this need, this article proposes a quantile version of SiZer for the regression setting. By inspecting the SiZer maps produced by this new SiZer, real quantile structures hidden in a dataset can be more effectively revealed, while at the same time spurious features can be filtered out. The utility of this quantile SiZer is illustrated via applications to both real data and simulated examples. This article has supplementary material online.
Publisher
AMER STATISTICAL ASSOC
Issue Date
2010-09
Language
English
Article Type
Article
Citation

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, v.19, no.3, pp.497 - 513

ISSN
1061-8600
DOI
10.1198/jcgs.2010.09120
URI
http://hdl.handle.net/10203/285761
Appears in Collection
MA-Journal Papers(저널논문)
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