Weak signals in high‐dimensional regression: Detection, estimation and prediction
Weak signals in high‐dimensional regression: Detection, estimation and prediction
Abstract Regularization methods, including Lasso, group Lasso, and SCAD, typically focus on selecting variables with strong effects while ignoring weak signals. This may result in biased prediction, especially when weak signals outnumber strong signals. This paper aims to incorporate weak signals in variable selection, estimation, and prediction. We propose a …