Nonmetric Linear Biplots

J. C. Gower, J. J. Meulman and G. M. Arnold

Journal of Classification, 1999, vol. 16, issue 2, 196 pages

Abstract: A methodology is developed for constructing linear biplots for a class of nonmetric multidimensional scaling methods for multivariate data. The nonlinear transformations of nonmetric scaling manifest themselves in irregularly spaced calibration markers. Two approaches are examined, one based on Procrustean embedding, the other on a modification of the popular regression method. The widespread use of an unmodified regression method in association with nonlinear transformations is questioned. An example is given. The methodology presented here could potentially be developed to give an optimal represention of a matrix in fewer geometric dimensions than its rank. Copyright Springer-Verlag New York Inc. 1999

Keywords: Biplots; calibration; Distance-based multivariate analysis; Least-squares scaling; Matrix approximation; Non-linear multivariate analysis; Non-metric multidimensional scaling; Ordination; Orthogonal Procrustes analysis; Principal components analysis; Regression method for biplots (search for similar items in EconPapers)
Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1007/s003579900053 (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:jclass:v:16:y:1999:i:2:p:181-196

Ordering information: This journal article can be ordered from
http://www.springer. ... hods/journal/357/PS2

DOI: 10.1007/s003579900053

Access Statistics for this article

Journal of Classification is currently edited by Douglas Steinley

More articles in Journal of Classification from Springer, The Classification Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().