BibTex Citation Data :
@article{J.Gauss29922, author = {Arya Arrasyid and Dwi Ispriyanti and Abdul Hoyyi}, title = {METODE MODIFIED JACKKNIFE RIDGE REGRESSION DALAM PENANGANAN MULTIKOLINIERITAS (STUDI KASUS INDEKS PEMBANGUNAN MANUSIA DI JAWA TENGAH)}, journal = {Jurnal Gaussian}, volume = {10}, number = {1}, year = {2021}, keywords = {Generalized Ridge Regression, Jackknife Ridge Regression, Modified Jackknife Ridge Regression, Multicolinearity}, abstract = { The human development index is a value where the value showed the measure of living standards comparison in a region. The Human Development Index is influenced by several factors, one of them is the education factor that is the average years of schooling and expected years of schooling. A statistical method to find the correlation between the independent variable and the dependent variable can be conducted using the linear regression method. Linear regression requires several assumptions, one of which is the multicollinearity assumption. If the multicollinearity assumption is not fulfilled, another alternative is needed to estimate the regression parameters. One method that can be used to estimate regression parameters is the ridge regression method with an ordinary ridge regression estimator. Ordinary ridge regression then developed more into several methods, such as generalized ridge regression, jackknife ridge regression, and modified jackknife ridge regression method. The generalized Ridge Regression method causes a reduction to variance in linear regression, while the jackknife ridge regression method is obtained by resampling jackknife process on the generalized ridge regression method. Modified jackknife ridge regression is a combination of generalized ridge regression and jackknife ridge regression method. In this journal, the three ridge regression methods will be compared based on the Mean Squared Error obtained in each method. The results of this study indicate that the jackknife ridge regression method has the smallest MSE value. Keywords : Generalized Ridge Regression, Jackknife Ridge Regression, Modified Jackknife Ridge Regression, Multicolinearity }, issn = {2339-2541}, pages = {104--113} doi = {10.14710/j.gauss.10.1.104-113}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/29922} }
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The human development index is a value where the value showed the measure of living standards comparison in a region. The Human Development Index is influenced by several factors, one of them is the education factor that is the average years of schooling and expected years of schooling. A statistical method to find the correlation between the independent variable and the dependent variable can be conducted using the linear regression method. Linear regression requires several assumptions, one of which is the multicollinearity assumption. If the multicollinearity assumption is not fulfilled, another alternative is needed to estimate the regression parameters. One method that can be used to estimate regression parameters is the ridge regression method with an ordinary ridge regression estimator. Ordinary ridge regression then developed more into several methods, such as generalized ridge regression, jackknife ridge regression, and modified jackknife ridge regression method. The generalized Ridge Regression method causes a reduction to variance in linear regression, while the jackknife ridge regression method is obtained by resampling jackknife process on the generalized ridge regression method. Modified jackknife ridge regression is a combination of generalized ridge regression and jackknife ridge regression method. In this journal, the three ridge regression methods will be compared based on the Mean Squared Error obtained in each method. The results of this study indicate that the jackknife ridge regression method has the smallest MSE value.
Keywords: Generalized Ridge Regression, Jackknife Ridge Regression, Modified Jackknife Ridge Regression, Multicolinearity
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