Post-Estimation Shrinkage in Full and Selected Linear Regression Models in Low-Dimensional Data Revisited
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The fit of a regression model to new data is often worse due to overfitting. Analysts use variable selection techniques to develop parsimonious regression models, which may introduce bias into regression estimates. Shrinkage methods have been proposed to mitig... ...
