Jurnal Aplikasi Statistika & Komputasi Statistik
Vol 8 No 2 (2016): Journal of Statistical Application and Computational Statistics

Metode Penanganan Multikolinieritas pada RLB: Perbandingan Partial Least Square dengan Ridge Regression

Putri, Yulia Atma (Unknown)
Anggorowati, Margaretha Ari (Unknown)



Article Info

Publish Date
31 Dec 2016

Abstract

Multicolinierity between variable predictor in multiple regression is assuming violation  for ordinary least square estimator (OLS). Ridge Regression (RR) and Partial Least Square Regression (PLSR were used to handle the multicolinierity problem. RR modify OLS by adding subjective bias consatant, while PLSR, generalize and combine Principal Component Analisis and multiple regression. The efficiency of these two methods will be compared based on the value of RMSE. This study simulated generating data in different level of multicolinearity, the number of variabel, and number of observation were controlled. This study results that, overall, both method equally efficient.

Copyrights © 2016






Journal Info

Abbrev

jurnalasks

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

Redaksi menerima karya ilmiah atau artikel penelitian mengenai kajian teori statistika dan komputasi statistik pada bidang ekonomi dan sosial dan kependudukan, serta teknologi informasi. Redaksi berhak menyunting tulisan tanpa mengubah makna subtansi tulisan. Isi jurnal Aplikasi Statistika dan ...