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dc.contributor.authorWilson, Paul
dc.contributor.authorEinbeck, Jochen
dc.date.accessioned2019-08-08T11:14:52Z
dc.date.available2019-08-08T11:14:52Z
dc.date.issued2021-01-27
dc.identifier.citationWilson, P. and Einbeck, J. (2021) A graphical tool for assessing the suitability of a count regression model, Austrian Journal of Statistics, 50, pp. 1–23.en
dc.identifier.issn1026-597Xen
dc.identifier.doi10.17713/ajs.v50i1.921
dc.identifier.urihttp://hdl.handle.net/2436/622632
dc.description.abstractWhilst many numeric methods, such as AIC and deviance, exist for assessing or comparing model fit, diagrammatic methods are few. We present here a diagnostic plot, which we refer to as a ‘Quantile Band plot’, that may be used to visually assess the suitability of a given count data model. In the case of diagnosed model inadequacy, the plot has the unique feature of conveying precise information on the character of the violation, hence pointing the data analyst towards a potentially better model choice.en
dc.formatapplication/PDFen
dc.language.isoenen
dc.publisherÖsterreichische Statistische Gesellschaft (Austrian Society for Statistics)en
dc.relation.urlhttps://www.ajs.or.at/index.php/ajsen
dc.subjectQuantile regressionen
dc.subjectZero-modified modelen
dc.subjectDiscretised lognormal distributionen
dc.subjectOrdinary least squares regressionen
dc.titleA graphical tool for assessing the suitability of a count regression modelen
dc.typeJournal articleen
dc.identifier.journalAustrian Journal of Statisticsen
dc.date.updated2019-08-07T15:23:59Z
dc.date.accepted2019-04-01
rioxxterms.funderUniversity of Wolverhampton
rioxxterms.identifier.projectUOW080819PWen
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2021-01-27en
dc.source.volume50
dc.source.issue1
refterms.dateFCD2019-08-08T11:11:56Z
refterms.versionFCDVoR
refterms.dateFOA2019-08-08T11:14:53Z


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