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A consistent nonparametric test of the convexity of regression based on least squares splines

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  • Diack, Cheikh A. T.

Abstract

This paper provides a test of convexity of a regression function. This test is based on the least squares splines. The test statistic is shown to be asymptotically of size equal to the nominal level, while diverging to infinity if the convexity is misspecified. Therefore, the test is consistent against all deviations from the null hypothesis.

Suggested Citation

  • Diack, Cheikh A. T., 1998. "A consistent nonparametric test of the convexity of regression based on least squares splines," SFB 373 Discussion Papers 1998,44, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:199844
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    References listed on IDEAS

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    1. Diack, C.A.T. & Thomas-Agnan, C., 1996. "A Nonparametric Test of The Non-Convexity of Regression," Papers 976.427, Toulouse - GREMAQ.
    2. Yatchew, Adonis John, 1992. "Nonparametric Regression Tests Based on Least Squares," Econometric Theory, Cambridge University Press, vol. 8(4), pages 435-451, December.
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