Improved Penalty Strategies in Linear Regression Models
DOI:
https://doi.org/10.57805/revstat.v15i2.212Keywords:
sub-model, Full Model, Pretest and Shrinkage Estimation, Multicollinearity, Asymptotic and SimulationAbstract
We suggest pretest and shrinkage ridge estimation strategies for linear regression models. We investigate the asymptotic properties of suggested estimators. Further, a Monte Carlo simulation study is conducted to assess the relative performance of the listed estimators. Also, we numerically compare their performance with Lasso, adaptive Lasso and SCAD strategies. Finally, a real data example is presented to illustrate the usefulness of the suggested methods.
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Copyright (c) 2017 REVSTAT-Statistical Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.