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Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition
Aside from distribution theory, projections and the singular value decomposition (SVD) are the two most important concepts for understanding the basic mechanism of multivariate analysis. The former underlies the least squares estimation in regression analysis, which is essentially a projection of on...
| Autores principales: | , , |
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| Lenguaje: | eng |
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Springer
2011
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| Acceso en línea: | https://dx.doi.org/10.1007/978-1-4419-9887-3 http://cds.cern.ch/record/1414711 |