PENDUGAAN KOEFISIEN REGRESI UNTUK DATA MENGANDUNG MULTIKOLINEARITAS MENGGUNAKAN PLS

Abstract

Correlation between predictor variables (multicollinearity) become a problem in regression analysis. There are some methods to solve the problem. Each method has complexity. One of those methods is PLS. This research aims to describe the procedur of Estimation of PLS regression. PLS combine principal component analysis and multiple linear regression. PLS method estimates regression coefficient by selecting the number of component that is used in the model that has optimum Mean Square Error (minimum MSE). Optimal MSE is taken from cross validation.