Testing the equality of nonparametric regression curves
Miguel Delgado ()
Statistics & Probability Letters, 1993, vol. 17, issue 3, 199-204
This paper proposes a test for the equality of nonparametric regression curves that does not depend on the choice of a smoothing number. The test statistic resembles in spirit the Kolmogorov-Smirnov statistic and it is easy to compute. It is powerful under alternatives that converge to the null hypothesis at a rate n-1/2. The disturbance distributions are arbitrary and possibly unequal, and conditions on the regressors distribution are very mild. A Monte Carlo study illustrates the performance of the test in small and moderate samples. We also study extensions to multiple regression, and test the equality of several regression curves.
Keywords: Nonparametric; testing; weighted; empirical; process; Donsker's; invariance; principle; Brownian; motion; local; alternatives (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:17:y:1993:i:3:p:199-204
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