Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/1995
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yanev, Petko I. | - |
dc.contributor.author | Kontoghiorghes, Erricos John | - |
dc.date.accessioned | 2013-01-28T13:15:31Z | en |
dc.date.accessioned | 2013-05-16T08:22:27Z | - |
dc.date.accessioned | 2015-12-02T09:32:46Z | - |
dc.date.available | 2013-01-28T13:15:31Z | en |
dc.date.available | 2013-05-16T08:22:27Z | - |
dc.date.available | 2015-12-02T09:32:46Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | Parallel Computing, 2008, vol. 34, iss. 6-8, pp. 451-468 | en_US |
dc.identifier.issn | 01678191 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/1995 | - |
dc.description.abstract | Computationally efficient parallel algorithms for downdating the least squares estimator of the ordinary linear regression are proposed. The algorithms, which are based on the QR decomposition, are block versions of sequential Givens strategies and efficiently exploit the triangular structure of the data matrices. The first strategy utilizes only part of the orthogonal matrix which is derived from the QR decomposition of the initial data matrix. The rest of the orthogonal matrix is not updated or explicitly computed. A modification of the parallel algorithm, which explicitly computes the whole orthogonal matrix in the downdated QR decomposition, is also considered. An efficient distribution of the matrices over the processors is proposed. Furthermore, the new algorithms do not require any inter-processor communication. The theoretical complexities are derived and experimental results are presented and analyzed. The parallel strategies are scalable and highly efficient for large scale downdating least squares problems. A new parallel block-hyperbolic downdating strategy is developed. The algorithm is rich in BLAS-3 computations, involves negligible duplicated computations and requires insignificant inter-processor communication. It is found to outperform the previous downdating strategies and to be highly efficient for large scale problems. The experimental results confirm the derived theoretical complexities. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation.ispartof | Parallel Computing | en_US |
dc.rights | © Elsevier | en_US |
dc.subject | Least squares | en_US |
dc.subject | Parallel algorithms | en_US |
dc.subject | Communication systems | en_US |
dc.subject | Problem solving | en_US |
dc.subject | Regression analysis | en_US |
dc.title | Parallel algorithms for downdating the least squares estimator of the regression model | en_US |
dc.type | Article | en_US |
dc.affiliation | Cyprus University of Technology | en |
dc.collaboration | Université de Neuchâtel | en_US |
dc.collaboration | University of Cyprus | en_US |
dc.collaboration | Plovdiv University Paisii Hilendarski | en_US |
dc.collaboration | Birkbeck University of London | en_US |
dc.subject.category | Economics and Business | en_US |
dc.journals | Subscription | en_US |
dc.country | Switzerland | en_US |
dc.country | Cyprus | en_US |
dc.country | Bulgaria | en_US |
dc.country | United Kingdom | en_US |
dc.subject.field | Social Sciences | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1016/j.parco.2008.01.002 | en_US |
dc.dept.handle | 123456789/54 | en |
dc.relation.issue | 6-8 | en_US |
dc.relation.volume | 34 | en_US |
cut.common.academicyear | 2007-2008 | en_US |
dc.identifier.spage | 451 | en_US |
dc.identifier.epage | 468 | en_US |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.fulltext | No Fulltext | - |
crisitem.journal.journalissn | 0167-8191 | - |
crisitem.journal.publisher | Elsevier | - |
crisitem.author.dept | Department of Finance, Accounting and Management Science | - |
crisitem.author.faculty | Faculty of Tourism Management, Hospitality and Entrepreneurship | - |
crisitem.author.orcid | 0000-0001-9704-9510 | - |
crisitem.author.parentorg | Faculty of Management and Economics | - |
Appears in Collections: | Άρθρα/Articles |
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