|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 10 van 15 gevonden artikelen
| Titel: |
Hierarchical clustering of variables: a comparison among strategies of analysis |
| Auteur: |
Soffritti, Gabriele |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 28 (1999) nr. 4 pagina's 977-999 |
| Jaar: |
1999 |
| Inhoud: |
In this paper some hierarchical methods for identifying groups of variables are illustrated and compared. It is shown that the use of multivariate association measures between two sets of variables can overcome the drawbacks of the usually employed bivariate correlation coefficient, but the resulting methods are generally not monotonic. Thus a new multivariate association measure is proposed, based on the links existing between canonical correlation analysis and principal component analysis, which can be more suitably used for the purpose at hand. The hierarchical method based on the suggested measure is illustrated and compared with other possible solutions by analysing simulated and real data sets. Finally an extension of the suggested method to the more general situation of mixed (qualitative and quantitative) variables is proposed and theoretically discussed. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 10 van 15 gevonden artikelen
| << vorige | volgende >> |