EconPapers    
Economics at your fingertips  
 

An investigation of feasible descent algorithms for estimating the condition number of a matrix

Carmo Brás (), William Hager () and Joaquim Júdice ()

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2012, vol. 20, issue 3, 809 pages

Abstract: Techniques for estimating the condition number of a nonsingular matrix are developed. It is shown that Hager’s 1-norm condition number estimator is equivalent to the conditional gradient algorithm applied to the problem of maximizing the 1-norm of a matrix-vector product over the unit sphere in the 1-norm. By changing the constraint in this optimization problem from the unit sphere to the unit simplex, a new formulation is obtained which is the basis for both conditional gradient and projected gradient algorithms. In the test problems, the spectral projected gradient algorithm yields condition number estimates at least as good as those obtained by the previous approach. Moreover, in some cases, the spectral gradient projection algorithm, with a careful choice of the parameters, yields improved condition number estimates. Copyright Sociedad de Estadística e Investigación Operativa 2012

Keywords: Condition number; Numerical linear algebra; Nonlinear programming; Gradient algorithms; 15A12; 49M37; 90C30 (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s11750-010-0161-9 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:topjnl:v:20:y:2012:i:3:p:791-809

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

DOI: 10.1007/s11750-010-0161-9

Access Statistics for this article

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Juan José Salazar González and Gustavo Bergantiños

More articles in TOP: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:topjnl:v:20:y:2012:i:3:p:791-809