Influence and sensitivity measures in correspondence analysis
Since correspondence analysis appears to be sensitive to outliers, it is important to be able to evaluate the sensitivity of the data on the results. This article deals with measuring the influence of rows and columns on the results obtained with correspondence analysis. To establish the influence of individuals on the analysis, we use the notion of influence curve and we propose a general criterion based on the mean square error to measure the sensitivity of the correspondence analysis and its robustness. A numerical example is presented to illustrate the notions developed in this article.
Saved in:
| Main Authors: | , |
|---|---|
| Format: | article biblioteca |
| Language: | eng |
| Subjects: | U10 - Informatique, mathématiques et statistiques, méthode statistique, http://aims.fao.org/aos/agrovoc/c_7377, |
| Online Access: | http://agritrop.cirad.fr/543442/ http://agritrop.cirad.fr/543442/1/543442.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|