Tests for independence in non-parametric heteroscedastic regression models
AbstractConsistent procedures are constructed for testing independence between the regressor and the error in non-parametric regression models. The tests are based on the Fourier formulation of independence, and utilize the joint and the marginal empirical characteristic functions of the regressor and of estimated residuals. The asymptotic null distribution as well as the behavior of the test statistic under alternatives is investigated. A simulation study compares bootstrap versions of the proposed tests to corresponding procedures utilizing the empirical distribution function.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 102 (2011)
Issue (Month): 4 (April)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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"Specification tests in nonparametric regression,"
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Elsevier, vol. 143(1), pages 88-102, March.
- Einmahl, J.H.J. & Keilegom, I. van, 2008.
"Tests for independence in nonparametric regression,"
Open Access publications from Tilburg University
urn:nbn:nl:ui:12-192434, Tilburg University.
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- Florens, Jean-Pierre & Simar, Léopold & Van Keilegom, Ingrid, 2014. "Frontier estimation in nonparametric location-scale models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 456-470.
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