Properties of BLUEs in full versus small linear models

Simple item page
dc.citation.issue21
dc.citation.volume52
dc.contributor.authorHaslett SJ
dc.contributor.authorMarkiewicz A
dc.contributor.authorPuntanen S
dc.date.accessioned2024-02-08T19:39:00Z
dc.date.accessioned2024-07-25T06:47:34Z
dc.date.available2022-03-29
dc.date.available2024-02-08T19:39:00Z
dc.date.available2024-07-25T06:47:34Z
dc.date.issued2023
dc.description.abstractIn this article we consider the partitioned linear model M12= {y,X1β1+X2β2,V} and the corresponding small model M1={y,X1β1,V}. We focus on comparing the best linear unbiased estimators, BLUEs, of X1β1 under M12 and M1. In other words, we are interested in the effect of adding regressors on the BLUEs. Particular attention is paid on the consistency of the model, that is, whether the realized value of the response vector y belongs to the column space of (X1:V) or (X1:X2:V)
dc.description.confidentialfalse
dc.format.pagination7684-7698
dc.identifier.citationHaslett SJ, Markiewicz A, Puntanen S. (2023). Properties of BLUEs in full versus small linear models. Communications in Statistics - Theory and Methods. 52. 21. (pp. 7684-7698).
dc.identifier.doi10.1080/03610926.2022.2052899
dc.identifier.eissn1532-415X
dc.identifier.elements-typejournal-article
dc.identifier.issn0361-0926
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/70880
dc.languageEnglish
dc.publisherTaylor and Francis Group
dc.publisher.urihttps://www.tandfonline.com/doi/full/10.1080/03610926.2022.2052899
dc.relation.isPartOfCommunications in Statistics - Theory and Methods
dc.rights(c) 2022 The Author/s
dc.rightsCC BY-NC-ND 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBest linear unbiased estimator
dc.subjectBLUE
dc.subjectLöwner ordering
dc.subjectpartitioned linear model
dc.subjectadding regressors
dc.titleProperties of BLUEs in full versus small linear models
dc.typeJournal article
pubs.elements-id452878
pubs.organisational-groupOther
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