The spectral decomposition of a covariance matrix for the balanced mixed analysis of variance model

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dc.contributor.authorGuven, Bilgehan
dc.date.accessioned2025-01-27T20:22:33Z
dc.date.available2025-01-27T20:22:33Z
dc.date.issued2012
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractWe derive the spectral decomposition of a covariance matrix for the balanced mixed analysis of variance model. The derivation is based on determining the distinct eigenvalues of a covariance matrix and then obtaining a principal idempotent matrix for each distinct eigenvalue. Examples are given to illustrate the results. (C) 2011 Elsevier Inc. All rights reserved.
dc.identifier.doi10.1016/j.laa.2011.11.028
dc.identifier.endpage3346
dc.identifier.issn0024-3795
dc.identifier.issue9
dc.identifier.scopus2-s2.0-84857994321
dc.identifier.scopusqualityQ1
dc.identifier.startpage3337
dc.identifier.urihttps://doi.org/10.1016/j.laa.2011.11.028
dc.identifier.urihttps://hdl.handle.net/20.500.12428/21944
dc.identifier.volume436
dc.identifier.wosWOS:000302852700030
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Inc
dc.relation.ispartofLinear Algebra and Its Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20250125
dc.subjectMixed analysis of variance model
dc.subjectCovariance matrix
dc.subjectEigenvalue and eigenvector
dc.subjectSpectral decomposition of a symmetric matrix
dc.titleThe spectral decomposition of a covariance matrix for the balanced mixed analysis of variance model
dc.typeArticle

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