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Estimability of variance components when all model matrices commute

dc.contributor.authorBailey, R.A.
dc.contributor.authorFerreira, Sandra S.
dc.contributor.authorFerreira, Dário
dc.contributor.authorNunes, Célia
dc.date.accessioned2020-02-07T14:12:17Z
dc.date.available2020-02-07T14:12:17Z
dc.date.issued2016
dc.description.abstractThis paper deals with estimability of variance components in mixed models when all model matrices commute. In this situation, it is well known that the best linear unbiased estimators of fixed effects are the ordinary least squares estimators. If, in addition, the family of possible variance–covariance matrices forms an orthogonal block structure, then there are the same number of variance components as strata, and the variance components are all estimable if and only if there are non-zero residual degrees of freedom in each stratum. We investigate the case where the family of possible variance–covariance matrices, while still commutative, no longer forms an orthogonal block structure. Now the variance components may or may not all be estimable, but there is no clear link with residual degrees of freedom. Whether or not they are all estimable, there may or may not be uniformly best unbiasedpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.laa.2015.11.002pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/9117
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectAnalysis of variancept_PT
dc.subjectCommutativitypt_PT
dc.subjectMixed modelpt_PT
dc.subjectOrthogonal block structurept_PT
dc.subjectSegregationpt_PT
dc.titleEstimability of variance components when all model matrices commutept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage160pt_PT
oaire.citation.startPage144pt_PT
oaire.citation.titleLinear Algebra and its Applicationspt_PT
oaire.citation.volume492pt_PT
person.familyNameFerreira
person.familyNameFerreira
person.familyNameNunes
person.givenNameSandra
person.givenNameDário
person.givenNameCélia
person.identifier1454084
person.identifierR-000-3NA
person.identifier.ciencia-idE01A-BAE7-2B14
person.identifier.ciencia-id9B1C-6DF8-2872
person.identifier.ciencia-idAC1F-3CA0-75FE
person.identifier.orcid0000-0002-9209-7772
person.identifier.orcid0000-0001-9095-0947
person.identifier.orcid0000-0003-0167-4851
person.identifier.ridH-1231-2016
person.identifier.scopus-author-id37088374700
person.identifier.scopus-author-id37088452300
person.identifier.scopus-author-id57194580125
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication476a0b22-7679-47cb-afe3-7f772abd7ba1
relation.isAuthorOfPublicationa46ed4b5-aea7-4dcb-bbbf-f2219d3a3cb9
relation.isAuthorOfPublication6c089279-689d-4566-b2ee-797ddbefbeab
relation.isAuthorOfPublication.latestForDiscovery476a0b22-7679-47cb-afe3-7f772abd7ba1

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