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https://hdl.handle.net/10419/22197
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Čížek, Pavel | en |
dc.contributor.author | Čížková, Lenka | en |
dc.date.accessioned | 2009-01-29T14:54:18Z | - |
dc.date.available | 2009-01-29T14:54:18Z | - |
dc.date.issued | 2004 | - |
dc.identifier.uri | http://hdl.handle.net/10419/22197 | - |
dc.description.abstract | Many methods of computational statistics lead to matrix-algebra or numerical- mathematics problems. For example, the least squares method in linear regression reduces to solving a system of linear equations. The principal components method is based on finding eigenvalues and eigenvectors of a matrix. Nonlinear optimization methods such as Newton?s method often employ the inversion of a Hessian matrix. In all these cases, we need numerical linear algebra. | en |
dc.language.iso | eng | en |
dc.publisher | |aHumboldt-Universität zu Berlin, Center for Applied Statistics and Economics (CASE) |cBerlin | en |
dc.relation.ispartofseries | |aPapers |x2004,23 | en |
dc.subject.ddc | 330 | en |
dc.title | Numerical Linear Algebra | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 495307289 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
dc.identifier.repec | RePEc:zbw:caseps:200423 | en |
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