Regresion PLS y PCA como solución al problema de multicolinealidad en regresión múltiple
Kaydedildi:
| Yazarlar: | , |
|---|---|
| Materyal Türü: | artículo original |
| Durum: | Versión publicada |
| Yayın Tarihi: | 2011 |
| Diğer Bilgiler: | We present and compare principal components regression and partial least squares regression, and their solution to the problem of multicollinearity. We illustrate the use of both techniques, and demonstrate the superiority of partial least squares. |
| Ülke: | Portal de Revistas UCR |
| Kurum: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Dil: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/2111 |
| Online Erişim: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/2111 |
| Anahtar Kelime: | principal components analysis partial least squares dimensionality reduction análisis de componentes principales mı́nimos cuadrados parciales reducción de la dimensionalidad |