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Comparison of non-parametric regression functions through their cumulatives

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  • Scheike, Thomas H.

Abstract

In this work we present a simple estimator for the cumulative regression function that involves no smoothing and we give its asymptotic distribution. By comparing cumulatives a test for comparison of nonparametric regression functions is proposed. The proposed test does not involve a smoothing parameter and has good power against alternatives that are uniformly ordered. The test-statistic works for both fixed and random designs.

Suggested Citation

  • Scheike, Thomas H., 2000. "Comparison of non-parametric regression functions through their cumulatives," Statistics & Probability Letters, Elsevier, vol. 46(1), pages 21-32, January.
    • Handle: RePEc:eee:stapro:v:46:y:2000:i:1:p:21-32
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    References listed on IDEAS

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    1. Delgado, Miguel A., 1993. "Testing the equality of nonparametric regression curves," Statistics & Probability Letters, Elsevier, vol. 17(3), pages 199-204, June.
    2. King, Eileen & Hart, Jeffrey D. & Wehrly, Thomas E., 1991. "Testing the equality of two regression curves using linear smoothers," Statistics & Probability Letters, Elsevier, vol. 12(3), pages 239-247, September.
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    Cited by:

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    2. Hira L. Koul & Fang Li, 2020. "Comparing two nonparametric regression curves in the presence of long memory in covariates and errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(4), pages 499-517, May.
    3. Gørgens, Tue, 2002. "Nonparametric comparison of regression curves by local linear fitting," Statistics & Probability Letters, Elsevier, vol. 60(1), pages 81-89, November.
    4. Srihera, Ramidha & Stute, Winfried, 2010. "Nonparametric comparison of regression functions," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2039-2059, October.

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