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Efficiency behaviour of kernel-smoothed kernel distribution function estimators

dc.contributor.authorJanssen, Paul
dc.contributor.authorSwanepoel, Jan W.H.
dc.contributor.authorVeraverbeke, Noël
dc.date.accessioned2020-04-20T10:18:08Z
dc.date.available2020-04-20T10:18:08Z
dc.date.issued2020
dc.identifier.citationJanssen, P. et al. 2020. Efficiency behaviour of kernel-smoothed kernel distribution function estimators. South African statistical journal, 54(1):15-23. [https://doi.org/10.37920/sasj.2020.54.1.2]en_US
dc.identifier.issn0038-271X
dc.identifier.urihttp://hdl.handle.net/10394/34568
dc.identifier.urihttps://hdl.handle.net/10520/EJC-1c22a4395a
dc.identifier.urihttps://doi.org/10.37920/sasj.2020.54.1.2
dc.description.abstractThe asymptotic mean integrated squared error (AMISE) and the kernel efficiency (KE) of kernel distribution function estimators are well studied. In this note we define new nonparametric distribution function estimators by kernel-smoothing an initial kernel distribution function estimator. We show that, under certain conditions, the AMISE and the KE can be improved. A concrete example and a Monte Carlo simulation are worked out for illustrationen_US
dc.language.isoenen_US
dc.publisherSASAen_US
dc.subjectAsymptotic mean integrated squared erroren_US
dc.subjectKernel distribution function estimatoren_US
dc.subjectKernel efficiencyen_US
dc.titleEfficiency behaviour of kernel-smoothed kernel distribution function estimatorsen_US
dc.typeArticleen_US
dc.contributor.researchID10177507 - Swanepoel, Jan Willem Hendrik
dc.contributor.researchID22051880 - Veraverbeke, Noël Daniel


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