Abstract
Given a configuration of n points in a Euclidean space and given a vector of similarity coefficients of an external object E with those n points, the problem is how to locate E among the n fixed points such that the higher the similarity of E with a point, the lower its distance from this point. Although this problem has been technically resolved by means of several types of procedures discussed below, it is nonetheless generally neglected. In the present article, we offer a theoretical and mathematical contribution to resolving this problem.
| Translated title of the contribution | External Variables as Points in Smallest Space Analysis: a Theoretical, Mathematical and Computer-Based Contribution |
|---|---|
| Original language | English |
| Pages (from-to) | 40-56 |
| Number of pages | 17 |
| Journal | BMS Bulletin of Sociological Methodology/ Bulletin de Methodologie Sociologique |
| Volume | 75 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jul 2002 |
Bibliographical note
Publisher Copyright:© 2002, SAGE Publications Ltd. All rights reserved.
Keywords
- Analyse de similitudes
- Distances
- Similarité
- Variables externes