Methods for the analysis of asymmetric pairwise relationships

Giuseppe Bove () and Akinori Okada ()
Additional contact information
Giuseppe Bove: Università Roma Tre
Akinori Okada: Tama University

Advances in Data Analysis and Classification, 2018, vol. 12, issue 1, No 2, 5-31

Abstract: Abstract Asymmetric pairwise relationships are frequently observed in experimental and non-experimental studies. They can be analysed with different aims and approaches. A brief review of models and methods of multidimensional scaling and cluster analysis able to deal with asymmetric proximities is provided taking a ‘data-analytic’ approach and emphasizing data visualization.

Keywords: Asymmetry; Multidimensional scaling; Visualization; Cluster analysis; 91C15 one-and multidimensional scaling; 91C20 Clustering; 62H25 Factor analysis and principal components; correspondence analysis; 62H30 Classification and discrimination; cluster analysis. (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11634-017-0307-9 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:advdac:v:12:y:2018:i:1:d:10.1007_s11634-017-0307-9

Ordering information: This journal article can be ordered from
http://www.springer. ... ds/journal/11634/PS2

DOI: 10.1007/s11634-017-0307-9

Access Statistics for this article

Advances in Data Analysis and Classification is currently edited by H.-H. Bock, W. Gaul, A. Okada, M. Vichi and C. Weihs

More articles in Advances in Data Analysis and Classification from Springer, German Classification Society - Gesellschaft für Klassifikation (GfKl), Japanese Classification Society (JCS), Classification and Data Analysis Group of the Italian Statistical Society (CLADAG), International Federation of Classification Societies (IFCS)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().