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Goodness-of-fit tests for parametric regression models based on empirical characteristic functions
Kybernetika, Tome 45 (2009) no. 6, pp. 960-971
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Test procedures are constructed for testing the goodness-of-fit in parametric regression models. The test statistic is in the form of an L2 distance between the empirical characteristic function of the residuals in a parametric regression fit and the corresponding empirical characteristic function of the residuals in a non-parametric regression fit. The asymptotic null distribution as well as the behavior of the test statistic under contiguous alternatives is investigated. Theoretical results are accompanied by a simulation study.
Test procedures are constructed for testing the goodness-of-fit in parametric regression models. The test statistic is in the form of an L2 distance between the empirical characteristic function of the residuals in a parametric regression fit and the corresponding empirical characteristic function of the residuals in a non-parametric regression fit. The asymptotic null distribution as well as the behavior of the test statistic under contiguous alternatives is investigated. Theoretical results are accompanied by a simulation study.
Classification : 62F05, 62G10, 62J05, 65C60
Keywords: empirical characteristic function; kernel regression estimators 
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Hušková, Marie; Meintanis, Simon G. Goodness-of-fit tests for parametric regression models based on empirical characteristic functions. Kybernetika, Tome 45 (2009) no. 6, pp. 960-971. http://geodesic.mathdoc.fr/item/KYB_2009_45_6_a5/

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