Some new aspects of taxicab correspondence analysis
Vartan Choulakian (),
Biagio Simonetti and
Thu Pham Gia
Statistical Methods & Applications, 2014, vol. 23, issue 3, 416 pages
Abstract:
Correspondence analysis (CA) and nonsymmetric correspondence analysis are based on generalized singular value decomposition, and, in general, they are not equivalent. Taxicab correspondence analysis (TCA) is a $$\hbox {L}_{1}$$ L 1 variant of CA, and it is based on the generalized taxicab singular value decomposition (GTSVD). Our aim is to study the taxicab variant of nonsymmetric correspondence analysis. We find that for diagonal metric matrices GTSVDs of a given data set are equivalent; from which we deduce the equivalence of TCA and taxicab nonsymmetric correspondence analysis. We also attempt to show that TCA stays as close as possible to the original correspondence matrix without calculating a dissimilarity (or similarity) measure between rows or columns. Further, we discuss some new geometric and distance aspects of TCA. Copyright Springer-Verlag Berlin Heidelberg 2014
Keywords: Taxicab correspondence analysis; Taxicab nonsymmetric correspondence analysis; Generalized taxicab singular value decomposition (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1007/s10260-014-0259-6 (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:stmapp:v:23:y:2014:i:3:p:401-416
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2
DOI: 10.1007/s10260-014-0259-6
Access Statistics for this article
Statistical Methods & Applications is currently edited by Tommaso Proietti
More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().