Robust model selection criteria for robust S and LTS estimators

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Hacettepe Journal of Mathematics and Statistics
Volume:45 Issue:1
Robust model selection criteria for robust S and LTS estimators

Robust model selection criteria for robust S and LTS estimators

Authors : Meral ÇETİN

Pages : 153-164

View : 46 | Download : 15

Publication Date : 2016-02-01

Article Type : Research Paper

Abstract :Outliers and multi-collinearity often have large influence in the model/variable selection process in linear regression analysis. To investigate this combined problem of multi-collinearity and outliers, we studied and compared Liu-type S insert ignore into journalissuearticles values(liuS-estimators); and Liu-type Least Trimmed Squares insert ignore into journalissuearticles values(liuLTS); estimators as robust model selection criteria. Therefore, the main goal of this study is to select subsets of independent variables which explain dependent variables in the presence of multi-collinearity, outliers and possible departures from the normality assumption of the error distribution in regression analysis using these models.
Keywords : Liu estimator, robust Liu estimator, M estimator, robust cp, robust Tp, robust model selection

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