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Numerical Linear Algebra

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  • Čížek, Pavel
  • Čížková, Lenka

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.

Suggested Citation

  • Čížek, Pavel & Čížková, Lenka, 2004. "Numerical Linear Algebra," Papers 2004,23, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    • Handle: RePEc:zbw:caseps:200423
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