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Testing the Equality of Nonparametric Regression Curves

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URI: https://hdl.handle.net/10016/2389
ISSN: 0167-7152
DOI: 10.1016/0167-7152(93)90167-H
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testing_SPL_1993.pdf (440.27 KB)
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1993
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Elsevier
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Abstract
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.
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Nonparametric, testing, weighted emperical process, Donsker's invariance principles
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Statistics and Probability Letters, 1993, vol.17, nº. 3, p. 199-204
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