Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/6771
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dc.contributor.authorYanev, Petko I.en
dc.contributor.authorKontoghiorghes, Erricos John-
dc.contributor.otherΚοντογιώργης, Έρρικος Γιάννης-
dc.date.accessioned2013-01-30T13:20:26Zen
dc.date.accessioned2013-05-16T08:22:25Z-
dc.date.accessioned2015-12-02T09:34:34Z-
dc.date.available2013-01-30T13:20:26Zen
dc.date.available2013-05-16T08:22:25Z-
dc.date.available2015-12-02T09:34:34Z-
dc.date.issued2006en
dc.identifier.citationParallel Computing ,2006, Volume 32, Issue 2, Pages 195-204en
dc.identifier.issn01678191en
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/6771en
dc.description.abstractComputationally efficient serial and parallel algorithms for estimating the general linear model are proposed. The sequential block-recursive algorithm is an adaptation of a known Givens strategy that has as a main component the Generalized QR decomposition. The proposed algorithm is based on orthogonal transformations and exploits the triangular structure of the Cholesky QRD factor of the variance-covariance matrix. Specifically, it computes the estimator of the general linear model by solving recursively a series of smaller and smaller generalized linear least squares problems. The new algorithm is found to outperform significantly the corresponding LAPACK routine. A parallel version of the new sequential algorithm which utilizes an efficient distribution of the matrices over the processors and has low inter-processor communication is developed. The theoretical computational complexity of the parallel algorithms is derived and analyzed. Experimental results are presented which confirm the theoretical analysis. The parallel strategy is found to be scalable and highly efficient for estimating large-scale general linear estimation problems.en
dc.formatpdfen
dc.language.isoenen
dc.publisherElsevieren
dc.rights© 2005 Elsevier B.V. All rights reserved.en
dc.subjectParallel algorithmsen
dc.subjectComputational complexityen
dc.subjectEstimationen
dc.subjectLinear systemsen
dc.subjectMathematical modelsen
dc.subjectProblem solvingen
dc.titleEfficient algorithms for estimating the general linear modelen
dc.typeArticleen
dc.affiliationCyprus University of Technologyen
dc.identifier.doihttp://dx.doi.org/10.1016/j.parco.2005.06.007en
dc.dept.handle123456789/54en
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
crisitem.author.deptDepartment of Commerce, Finance and Shipping-
crisitem.author.facultyFaculty of Management and Economics-
crisitem.author.orcid0000-0001-9704-9510-
crisitem.author.parentorgFaculty of Management and Economics-
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