Visualizing multiple quantile plots

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)69-78
Journal / PublicationJournal of Computational and Graphical Statistics
Volume22
Issue number1
Publication statusPublished - 2013
Externally publishedYes

Abstract

Multiple-quantile plots provide a powerful graphical method for comparing the distributions of two or more populations. This article develops a method of visualizing triple-quantile plots and their associated confidence tubes, thus extending the notion of a quantile-quantile (QQ) plot to three dimensions. More specifically, we consider three independent one-dimensional random samples with corresponding quantile functions Q1, Q2, and Q3. The triple-quantile (QQQ) plot is then defined as the threedimensional curve Q(p) = (Q1(p),Q2(p),Q3(p)), where 0 < p < 1. The empirical likelihood method is used to derive simultaneous distribution-free confidence tubes for Q. We apply our method to an economic case study of strike durations and to an epidemiological study involving the comparison of cholesterol levels among three populations. These data as well as the Mathematica code for computation of the tubes are available in the online supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

Research Area(s)

  • Confidence region, Empirical likelihood, Three-sample comparison

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

Visualizing multiple quantile plots. / Boon, Marko A. A.; Einmahl, John H. J.; McKeague, Ian W.

In: Journal of Computational and Graphical Statistics, Vol. 22, No. 1, 2013, p. 69-78.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review