Regresion PLS y PCA como Solucion al Problema de Multicolinealidad en Regresion Multiple

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.

Main Authors: Vega Vilca, José Carlos, Guzman, Josué
Format: Artículo
Language: Español
Published: 2015
Online Access: http://revistas.ucr.ac.cr/index.php/matematica/article/view/2111
http://hdl.handle.net/10669/12982
Summary: 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.