Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26351
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dc.contributor.authorWong, Hen_US
dc.contributor.authorLiu, Fen_US
dc.contributor.authorChen, Men_US
dc.contributor.authorIp, WCen_US
dc.date.accessioned2015-05-26T08:10:44Z-
dc.date.available2015-05-26T08:10:44Z-
dc.date.issued2009-
dc.identifier.citationComputational statistics and data analysis, 2009, v. 53, no. 9, p. 3466-3477en_US
dc.identifier.urihttp://hdl.handle.net/10397/26351-
dc.description.abstractIn this paper, we propose a diagnostic technique for checking heteroscedasticity based on empirical likelihood for the partial linear models. We construct an empirical likelihood ratio test for heteroscedasticity. Also, under mild conditions, a nonparametric version of Wilk's theorem is derived, which says that our proposed test has an asymptotic chi-square distribution. Simulation results reveal that the finite sample performance of our proposed test is satisfactory in both size and power. An empirical likelihood bootstrap simulation is also conducted to overcome the size distortion in small sample sizes.en_US
dc.description.sponsorshipDepartment of Applied Mathematicsen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputational Statistics and Data Analysisen_US
dc.titleEmpirical likelihood based diagnostics for heteroscedasticity in partial linear modelsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage3466-
dc.identifier.epage3477-
dc.identifier.volume53-
dc.identifier.issue9-
dc.identifier.doi10.1016/j.csda.2009.02.029-
dc.identifier.isiWOS:000266381800018-
dc.identifier.scopus2-s2.0-64749103287-
dc.identifier.rosgroupidr42032-
dc.description.ros2008-2009 > Academic research: refereed > Publication in refereed journal-
Appears in Collections:Journal/Magazine Article
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