An Algorithm for l∞ Regression with Quadratic Complexity
J. Ji and
C. Kicey
Additional contact information
J. Ji: Valdosta State University
C. Kicey: Valdosta State University
Journal of Optimization Theory and Applications, 2002, vol. 112, issue 3, No 6, 574 pages
Abstract:
Abstract Using a few very basic observations, we proposed recently a direct and finite algorithm for the computation of the l ∞ regression line on a discrete set $$\left\{ {(x_i ,y_i )} \right\}_i^n $$ under the assumption that $$x_1
Keywords: Linear regression; l ∞ norm; polynomial algorithm; quadratic complexity (search for similar items in EconPapers)
Date: 2002
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1023/A:1017916132749 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:joptap:v:112:y:2002:i:3:d:10.1023_a:1017916132749
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1023/A:1017916132749
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().