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dc.contributor.authorWilson, Paul
dc.contributor.editorEilers, Paul H. C.
dc.date.accessioned2019-07-29T15:13:59Z
dc.date.available2019-07-29T15:13:59Z
dc.date.issued2008-07-07
dc.identifier.citationWilson, P. (2008) The Dragnet Test: A New Approach to Choosing Between Models, in Eilers, Paul H. C. (ed.) Proceedings of the 23rd International Workshop on Statistical Modelling, July 7-11, 2008, Utrecht.. Utrecht: Statistical Modelling Society, pp. 448-453.en
dc.identifier.urihttp://hdl.handle.net/2436/622608
dc.description.abstractTraditional log-likelihood based methods for choosing between models, be they nested or non-nested, all concentrate on log -likelihoods evaluated at the maximum likelihood estimates of the model parameters. The true model parameters may in fact differ considerably from their maximum likelihood estimates. We propose a method that examines the relative fits of the models over a cross-section of likely parameter values; this method is based upon testing simple hypotheses, and hence avoids pitfalls associated with compound null hypotheses such as biased estimation of p-values.en
dc.formatapplication/PDFen
dc.language.isoenen
dc.publisherStatistical Modelling Societyen
dc.relation.urlhttp://www.statmod.org/files/proceedings/iwsm2008_proceedings.pdfen
dc.subjectnested-modelsen
dc.subjecthybrid testen
dc.subjectmodel discriminationen
dc.subjecthypothesis testingen
dc.subjectnon-nested modelsen
dc.titleThe Dragnet Test: A New Approach to Choosing Between Modelsen
dc.typeConference contributionen
dc.date.updated2019-07-26T14:21:03Z
dc.conference.name23rd International Workshop on Statistical Modelling
dc.conference.locationUtrecht
pubs.finish-date2008-07-11
pubs.start-date2008-07-07
dc.date.accepted2008-03-06
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW290719PWen
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2019-07-29en
dc.source.beginpage448
dc.source.endpage453
refterms.dateFCD2019-07-29T15:13:51Z
refterms.versionFCDVoR
refterms.dateFOA2019-07-29T15:14:00Z


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