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dc.contributor.authorWilson, Paul
dc.contributor.authorEinbeck, Jochen
dc.contributor.editorDupuys, Jean-François
dc.contributor.editorJosse, Julie
dc.date.accessioned2019-08-08T09:42:44Z
dc.date.available2019-08-08T09:42:44Z
dc.date.issued2016-07-04
dc.identifier.citationWilson, P. and Einbeck, J. (2016) On statistical testing and mean parameter estimation for zero–modification in count data regression, in Dupuys, J. and Josse, J. (eds.) Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France, pp. 327-332.en
dc.identifier.urihttp://hdl.handle.net/2436/622628
dc.description.abstractFor the problem of testing for zero–modification in Poisson regression, a simple and intuitive test can be constructed by computing directly confidence intervals for the number of 0’s under the Poisson assumption. This requires the ability of estimating the mean function accurately even if the data are in fact zero–inflated or deflated. A novel hybrid estimator is introduced for this purpose, which is of interest beyond the scope of the motivating test problem.en
dc.formatapplication/PDFen
dc.language.isoenen
dc.publisherStatistical Modelling Societyen
dc.relation.urlhttp://www.statmod.org/workshops_archive_proceedings_2016.htmen
dc.subjectHypothesis testingen
dc.subjectZero-modified modelen
dc.subjectZero-truncated modelen
dc.titleOn statistical testing and mean parameter estimation for zero–modification in count data regressionen
dc.typeConference contributionen
dc.date.updated2019-08-06T16:30:16Z
dc.conference.name31st International Workshop on Statistical Modelling
dc.conference.locationRennes
pubs.finish-date2016-07-08
pubs.start-date2016-07-04
dc.date.accepted2016-03-10
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW080819PWen
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2019-08-08en
dc.source.beginpage327
dc.source.endpage332
refterms.dateFCD2019-08-08T09:42:29Z
refterms.versionFCDVoR
refterms.dateFOA2019-08-08T09:42:45Z


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