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Numerical Linear Algebra

Pavel Cizek and Lenka Čížková

No 2004,23, Papers from Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE)

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.

Date: 2004
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