|
EconStor >
Humboldt-Universität Berlin >
CASE - Center for Applied Statistics and Economics, Humboldt-Universität Berlin >
Papers, CASE - Center for Applied Statistics and Economics, HU Berlin >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/22197
|
| | |
| Title: | | Numerical Linear Algebra  |
| Authors: | | Čížek, Pavel Čížková, Lenka |
| Issue Date: | | 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 |
| Appears in Collections: | | Papers, CASE - Center for Applied Statistics and Economics, HU Berlin
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/22197
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|