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Visualizing Multiple Quantile Plots

Author

Listed:
  • Boon, M.
  • Einmahl, J.H.J.

    (Tilburg University, Center For Economic Research)

  • McKeague, I.W.

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 Q 1 , Q 2 , and Q 3 . The triple-quantile (QQQ) plot is then defined as the threedimensional curve Q(p) = (Q 1 (p), Q 2 (p), Q 3 (p)), where 0 (This abstract was borrowed from another version of this item.)
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Suggested Citation

  • Boon, M. & Einmahl, J.H.J. & McKeague, I.W., 2011. "Visualizing Multiple Quantile Plots," Discussion Paper 2011-085, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:ef2fd92d-b063-4efe-b8b9-31ba8ed79272
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    File URL: https://pure.uvt.nl/ws/portalfiles/portal/1342525/2011-085.pdf
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    References listed on IDEAS

    as
    1. Beirlant, Jan & Deheuvels, Paul, 1990. "On the approximation of P--P and Q--Q plot processes by brownian bridges," Statistics & Probability Letters, Elsevier, vol. 9(3), pages 241-251, March.
    2. Einmahl, J.H.J. & McKeague, I.W., 1999. "Confidence tubes for multiple quantile plots via empirical likelihood," Other publications TiSEM b64493f8-1c01-40fd-b16d-7, Tilburg University, School of Economics and Management.
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    More about this item

    Keywords

    Confidence region; empirical likelihood; quantile plot; three-sample com- parison;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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