1. Ktisis Cyprus University of Technology
  2. Cyprus University of Technology (Research Output)
  3. Άρθρα/Articles
Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14964
DC FieldValueLanguage
dc.contributor.authorKonstantinou, Maria-
dc.contributor.authorDette, H.-
dc.date.accessioned2019-08-22T10:25:28Z-
dc.date.available2019-08-22T10:25:28Z-
dc.date.issued2015-10-23-
dc.identifier.citationBiometrika, 2015, vol. 102, no. 4, pp. 951-958.en_US
dc.identifier.issn00063444-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/14964-
dc.description.abstract© 2015 Biometrika Trust. We consider the construction of optimal designs for nonlinear regression models when there are measurement errors in the covariates. Corresponding approximate design theory is developed for maximum likelihood and least-squares estimation, with the latter leading to nonconcave optimization problems. Analytical characterizations of the locally D-optimal saturated designs are provided for the Michaelis-Menten, Emax and exponential regression models. Through concrete applications, we illustrate how measurement errors in the covariates affect the optimal choice of design and show that the locally D-optimal saturated designs are highly efficient for relatively small misspecifications of the parameter values.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.relation.ispartofBiometrikaen_US
dc.rights© Biometrika Trusten_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectClassical erroren_US
dc.subjectD-optimalityen_US
dc.subjectMeasurement error modelen_US
dc.subjectOptimal designen_US
dc.titleLocally optimal designs for errors-in-variables modelsen_US
dc.typeArticleen_US
dc.collaborationRuhr-Universität Bochumen_US
dc.subject.categoryEnvironmental Biotechnologyen_US
dc.subject.categoryOther Agricultural Sciencesen_US
dc.countryGermanyen_US
dc.subject.fieldAgricultural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1093/biomet/asv048en_US
dc.identifier.scopus2-s2.0-84950325444-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84950325444-
dc.relation.issue4en_US
dc.relation.volume102en_US
cut.common.academicyear2015-2016en_US
dc.identifier.spage951en_US
dc.identifier.epage958en_US
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1464-3510-
crisitem.journal.publisherOxford University Press-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.orcid0000-0002-4140-0444-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
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