A simulation study of the bias of parameter estimators in multivariate nonlinear models

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dc.contributor.authorGenç, Aşir
dc.date.accessioned2020-03-26T16:26:46Z
dc.date.available2020-03-26T16:26:46Z
dc.date.issued1999
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn nonlinear models, the estimation cannot be expressed analytically and some asymptotic expressions are used for parameter estimators in nonlinear models. In this study, bootstrap and jackknife methods are used to reduce the bias of estimators in nonlinear models for small samples.en_US
dc.identifier.endpage114en_US
dc.identifier.issn1300-4263en_US
dc.identifier.startpage105en_US
dc.identifier.urihttp://www.trdizin.gov.tr/publication/paper/detail/TXpRM01EYzM=
dc.identifier.urihttps://hdl.handle.net/20.500.12395/16882
dc.identifier.volume28en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofHacettepe Bulletin of Natural Sciences and Engineering Series B / Mathematics and Statisticsen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectMatematiken_US
dc.titleA simulation study of the bias of parameter estimators in multivariate nonlinear modelsen_US
dc.typeOtheren_US

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