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Nonparametric comparison of quantile curves: a stochastic process approach

Author

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  • Holger Dette
  • Jens Wagener
  • Stanislav Volgushev

Abstract

A new test for comparing conditional quantile curves is proposed which is able to detect Pitman alternatives converging to the null hypothesis at the optimal rate. The basic idea of the test is to measure differences between the curves by a process of integrated nonparametric estimates of the quantile curve. We prove weak convergence of this process to a Gaussian process and study the finite sample properties of a Kolmogorov-Smirnov test by means of a simulation study.

Suggested Citation

  • Holger Dette & Jens Wagener & Stanislav Volgushev, 2013. "Nonparametric comparison of quantile curves: a stochastic process approach," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(1), pages 243-260, March.
    • Handle: RePEc:taf:gnstxx:v:25:y:2013:i:1:p:243-260
    DOI: 10.1080/10485252.2012.732223
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    Cited by:

    1. Long Feng & Changliang Zou & Zhaojun Wang & Lixing Zhu, 2015. "Robust comparison of regression curves," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 185-204, March.

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