The problem of multicollinearity in multiple linear regression analysis gives unreliable estimates for regression parameters with least squares methods. In addition, outliers in data set cause to lose characteristics of best, unbiased, consistent of least squares estimation. In the presence of multicollinearity and outliers in the data set, it is suggested using biased methods based on robust estimators. In this study, for the data set including outliers both x and y directed, ridge regression analysis based on some robust techniques (M, Least Trimmed Sums of Squares, Least Median of Squares, S and Generalized M ) is applied and the results are considered as comparatively.
Alan : Sosyal, Beşeri ve İdari Bilimler
Dergi Türü : Ulusal
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