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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Ridge Regression Based On Some Robust Estimators, Hatice Samkar, Ozlem Alpu
Ridge Regression Based On Some Robust Estimators, Hatice Samkar, Ozlem Alpu
Journal of Modern Applied Statistical Methods
Robust ridge methods based on M, S, MM and GM estimators are examined in the presence of multicollinearity and outliers. GMWalker, using the LS estimator as the initial estimator is used. S and MM estimators are also used as initial estimators with the aim of evaluating the two alternatives as biased robust methods.
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Sample balancing is widely used in applied research to adjust a sample data to achieve better correspondence to Census statistics. The classic Deming-Stephan iterative proportional approach finds the weights of observations by fitting the cross-tables of sample counts to known margins. This work considers a bi-criteria objective for finding weights with maximum possible effective base size. This approach is presented as a ridge regression with the exponential nonlinear parameterization that produces nonnegative weights for sample balancing.