Abstract
Consistent procedures are constructed for testing the goodness-of-fit of the error distribution in nonparametric regression models. The test starts with a kernel-type regression fit and proceeds with the construction of a test statistic in the form of an L 2 distance between a parametric and a nonparametric estimates of the residual characteristic function. The asymptotic null distribution and the behavior of the test statistic under alternatives are investigated. A simulation study compares bootstrap versions of the proposed test to corresponding procedures utilizing the empirical distribution function.
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The work of the first author was supported by grant MSM 0021620839 and GAČR 201/06/0186.
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Hušková, M., Meintanis, S.G. Tests for the error distribution in nonparametric possibly heteroscedastic regression models. TEST 19, 92–112 (2010). https://doi.org/10.1007/s11749-008-0135-5
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DOI: https://doi.org/10.1007/s11749-008-0135-5