Approaches to robust estimation in the simplest variance components model

dc.contributor.authorStahel, Werner A.en
dc.contributor.authorWelsh, Alanen
dc.date.accessioned2026-01-01T10:42:13Z
dc.date.available2026-01-01T10:42:13Z
dc.date.issued1997-02-01en
dc.description.abstractThe simplest case of a random effects or variance components model is given by g groups with random location. We apply several general principles which can help to obtain robust methods to this situation. Two approaches, introduced by Rocke (Biometrika 70 (1983) 303-309) and Fellner (Technometrics 28 (1985) 51-60) are described and elaborated. A small simulation study suggests that considerable gains can be obtained by using robust procedures.en
dc.description.statusPeer-revieweden
dc.format.extent25en
dc.identifier.issn0378-3758en
dc.identifier.scopus0031065931en
dc.identifier.urihttps://hdl.handle.net/1885/733799827
dc.language.isoenen
dc.sourceJournal of Statistical Planning and Inferenceen
dc.subjectApproaches to robust statisticsen
dc.subjectHuberizingen
dc.subjectRandom effectsen
dc.subjectRobust maximum likelihooden
dc.titleApproaches to robust estimation in the simplest variance components modelen
dc.typeJournal articleen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage319en
local.bibliographicCitation.startpage295en
local.contributor.affiliationStahel, Werner A.; Swiss Federal Institute of Technology Zurichen
local.contributor.affiliationWelsh, Alan; Research School of Finance, Actuarial Studies and Statistics, Research School of Finance, Actuarial Studies & Statistics, ANU College of Business & Economics, The Australian National Universityen
local.identifier.citationvolume57en
local.identifier.doi10.1016/s0378-3758(96)00050-xen
local.identifier.pure4a270594-ab5d-4cfc-929e-707202b6d98een
local.identifier.urlhttps://www.scopus.com/pages/publications/0031065931en
local.type.statusPublisheden

Downloads