Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22197
Authors: 
Čížek, Pavel
Čížková, Lenka
Year of Publication: 
2004
Series/Report no.: 
Papers / Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) 2004,23
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.
Document Type: 
Working Paper

Files in This Item:
File
Size
311.96 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.