Penerapan Metode Generalized Ridge Regression dalam Mengatasi Masalah Multikolinearitas

Ir. I Putu Eka Nila Kencana, MT, I Putu Eka Nila Kencana (2013) Penerapan Metode Generalized Ridge Regression dalam Mengatasi Masalah Multikolinearitas. E - Jurnal Matematika, 2 (1). ISSN 1693-1394

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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

Item Type: Article
Uncontrolled Keywords: Linear regression, parameter estimation, multicoll
Subjects: L Education > L Education (General)
Divisions: Faculty of Law, Arts and Social Sciences > School of Education
Depositing User: Mr. Repository Admin
Date Deposited: 07 Jun 2016 21:58
Last Modified: 21 Jun 2016 05:58

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