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dc.contributor.authorJanssen, Paul
dc.contributor.authorSwanepoel, Jan
dc.contributor.authorVeraverbeke, Noël
dc.date.accessioned2017-04-18T13:06:49Z
dc.date.available2017-04-18T13:06:49Z
dc.date.issued2016
dc.identifier.citationJanssen, P. et al. 2016. Bernstein estimation for a copula derivative with application to conditional distribution and regression functionals. Test, 25(2):351-374. [https://doi.org/10.1007/s11749-015-0459-x]en_US
dc.identifier.issn1133-0686
dc.identifier.issn1863-8260 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/21445
dc.identifier.urihttps://doi.org/10.1007/s11749-015-0459-x
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs11749-015-0459-x
dc.description.abstractBernstein estimators attracted considerable attention as smooth nonparametric estimators for distribution functions, densities, copulas and copula densities. The present paper adds a parallel result for the first-order derivative of a copula function. This result then leads to Bernstein estimators for a conditional distribution function and its important functionals such as the regression and quantile functions. Results of independent interest have been derived such as an almost sure oscillation behavior of the empirical copula process and a Bahadur-type almost sure asymptotic representation for the Bernstein estimator of a regression quantile function. Simulations demonstrate the good performance of the proposed estimatorsen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectAsymptotic normalityen_US
dc.subjectAsymptotic representationen_US
dc.subjectBernstein estimationen_US
dc.subjectCopulaen_US
dc.subjectCopula densityen_US
dc.subjectOscillation of empirical copula processen_US
dc.subjectQuantile functionen_US
dc.titleBernstein estimation for a copula derivative with application to conditional distribution and regression functionalsen_US
dc.typeArticleen_US
dc.contributor.researchID10177507 - Swanepoel, Jan Willem Hendrik
dc.contributor.researchID22051880 - Veraverbeke, Noël Daniel


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