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Shrinkage Estimation Strategies in Generalized Ridge Regression Models Under Low/High-Dimension Regime

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 نشر من قبل Bahadir Y\\\"uzba\\c{s}i
 تاريخ النشر 2017
  مجال البحث الاحصاء الرياضي
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In this study, we propose shrinkage methods based on {it generalized ridge regression} (GRR) estimation which is suitable for both multicollinearity and high dimensional problems with small number of samples (large $p$, small $n$). Also, it is obtained theoretical properties of the proposed estimators for Low/High Dimensional cases. Furthermore, the performance of the listed estimators is demonstrated by both simulation studies and real-data analysis, and compare its performance with existing penalty methods. We show that the proposed methods compare well to competing regularization techniques.



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