Regresión y análisis factoriales
Guardado en:
| Autor: | |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2000 |
| Descripción: | Some recent developments in factor analysis of multi-sets are introduced in this short course. The more usual factor analyses are based on the singular values de-composition. So, the analyses of two matrices here are introduced from a qualitative criterion, for a non redundancy of partial relations between "common factors". A proposal for extending the simple linear regression, here considered between the two sets of the individuals which define the two sets of variables, lead to specific measures for each matrix. Some juxtapositions of graphics then are justified. The whole previous approach is extended for analyzing the dependency of K matrices with one matrix. The ACOM of Chessel and Hanafi (1996) then is considered as a PCA of sets of variables. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/179 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/179 |
| Palabra clave: | dependence between sets of variables non redondancy simultaneity biplots ordinary least squares correlation simple linear regression dependencia entre conjuntos de variables no redundancia simultaneidad mínimos cuadrados ordinarios correlación regresión lineal simple |