IDEAS home Printed from
   My bibliography  Save this article

Testing for one-sided alternatives in nonparametric censored regression


  • Cédric Heuchenne
  • Juan Pardo-Fernández



Assume that we have two populations (X 1 ,Y 1 ) and (X 2 ,Y 2 ) satisfying two general nonparametric regression models Y j =m j (X j )+ε j , j=1,2, where m(⋅) is a smooth location function, ε j has zero location and the response Y j is possibly right-censored. In this paper, we propose to test the null hypothesis H 0 :m 1 =m 2 versus the one-sided alternative H 1 :m 1 >m 2 . We introduce two test statistics for which we obtain the asymptotic normality under the null and the alternative hypotheses. Although the tests are based on nonparametric techniques, they can detect any local alternative converging to the null hypothesis at the parametric rate n −1/2 . The practical performance of a bootstrap version of the tests is investigated in a simulation study. An application to a data set about unemployment duration times is also included. Copyright Sociedad de Estadística e Investigación Operativa 2012

Suggested Citation

  • Cédric Heuchenne & Juan Pardo-Fernández, 2012. "Testing for one-sided alternatives in nonparametric censored regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 498-518, September.
  • Handle: RePEc:spr:testjl:v:21:y:2012:i:3:p:498-518
    DOI: 10.1007/s11749-011-0260-4

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Srihera, Ramidha & Stute, Winfried, 2010. "Nonparametric comparison of regression functions," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2039-2059, October.
    2. Natalie Neumeyer, 2009. "Smooth Residual Bootstrap for Empirical Processes of Non-parametric Regression Residuals," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 204-228.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:21:y:2012:i:3:p:498-518. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.