Testing the equality of nonparametric regression curves
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.
Year of publication: |
1993
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Authors: | Delgado, Miguel A. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 17.1993, 3, p. 199-204
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Publisher: |
Elsevier |
Keywords: | Nonparametric testing weighted empirical process Donsker's invariance principle Brownian motion local alternatives |
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