Authors:

NI KETUT TRI UTAMI, I KOMANG GDE SUKARSA

Abstract:

“Ordinary least square is parameter estimation method for linier regression analysis by minimizing residual sum of square. In the presence of multicollinearity, estimators which are unbiased and have a minimum variance can not be generated. Multicollinearity refers to a situation where regressor variables are highly correlated. Generalized Ridge Regression is an alternative method to deal with multicollinearity problem. In Generalized Ridge Regression, different biasing parameters for each regressor variables were added to the least square equation after transform the data to the space of orthogonal regressors. The analysis showed that Generalized Ridge Regression was satisfactory to overcome multicollinearity.”

Keywords

Keyword Not Available

Downloads:

Download data is not yet available.

References

References Not Available

PDF:

https://jurnal.harianregional.com/mtk/full-4924

Published

2013-01-30

How To Cite

UTAMI, NI KETUT TRI; SUKARSA, I KOMANG GDE. PENERAPAN METODE GENERALIZED RIDGE REGRESSION DALAM MENGATASI MASALAH MULTIKOLINEARITAS.E-Jurnal Matematika, [S.l.], v. 2, n. 1, p. 54-59, jan. 2013. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-4924. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/MTK.2013.v02.i01.p029.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 2 No 1 (2013): E-Jurnal Matematika

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License