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Adaptive Nonparametric Procedures and Applications

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  • N. J. Hill
  • A. R. Padmanabhan
  • Madan L. Puri

Abstract

Two adaptive nonparametric procedures are proposed for multiple comparisons and testing for ordered alternatives in the one‐way ANOVA model. The first procedure resembles a proposal of Hogg, Fisher and Randles (for hypothesis testing) while the second is a variation of the first. Applications to data on lung cancer illustrate the theory.The supremacy of these procedures over the parametric normal theory procedures and the rank‐based procedures is established. Monte Carlo studies show that these procedures can be safely applied when the size of each sample is at least 20.

Suggested Citation

  • N. J. Hill & A. R. Padmanabhan & Madan L. Puri, 1988. "Adaptive Nonparametric Procedures and Applications," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(2), pages 205-218, June.
    • Handle: RePEc:bla:jorssc:v:37:y:1988:i:2:p:205-218
    DOI: 10.2307/2347340
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    Cited by:

    1. Maurya, Vishal & Goyal, Anju & Gill, Amar Nath, 2011. "Simultaneous testing for the successive differences of exponential location parameters under heteroscedasticity," Statistics & Probability Letters, Elsevier, vol. 81(10), pages 1507-1517, October.
    2. Beier, F. & Buning, H., 1997. "An adaptive test against ordered alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 441-452, September.
    3. Herbert Büning, 2002. "An adaptive distribution-free test for the general two-sample problem," Computational Statistics, Springer, vol. 17(2), pages 297-313, July.
    4. Mahmood Kharrati-Kopaei & Ahad Malekzadeh, 2019. "On the exact distribution of the likelihood ratio test for testing the homogeneity of scale parameters of several two-parameter exponential distributions: complete and censored samples," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 409-427, May.

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