MODEL SELECTION VIA ROBUST VERSION OF R-SQUARED
@article{Saleh2014MODELSV, title={MODEL SELECTION VIA ROBUST VERSION OF R-SQUARED}, author={Shokrya Saleh}, journal={Journal of Mathematics and Statistics}, year={2014}, volume={10}, pages={414-420} }
R-squared ( R 2 ) is a popular method for variable selection in lin ear regression models. R 2 based on Least Squares (LS) regression minimizes the sum of the sq uared residuals; LS is sensitive to outlier observation. Alternative criterion based on M-estimators, which is less sensitive to outlying ob servation has been proposed. In this study explicit expression for suc h criterion is obtained when the Least Trimmed Squares (LTS) estimator is used. The influence function of R 2 is also…
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