The L1 Method

Richard L. Branham
Additional contact information
Richard L. Branham: Jefe Area Matematicas y Del Centro Regional de Investigaciones Científicas y Tecnológicas

Chapter Chapter 6 in Scientific Data Analysis, 1990, pp 133-167 from Springer

Abstract: Abstract In Chapter 4 we pointed out that the L 1 criterion, i.e., minimize the sum of the absolute values of the residualsis, 6.1 $$ {{\left\| r \right\|}_{1}} = {{\left\| {A\cdot X - d} \right\|}_{1}} = \min , $$ because of its robustness, extremely useful for data reduction. Where does this robustness come from? The answer to this question will be given in several stages.

Date: 1990
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-1-4612-3362-6_6

Ordering information: This item can be ordered from
http://www.springer.com/9781461233626

DOI: 10.1007/978-1-4612-3362-6_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().