A sorted penalty estimator: Inference for a correlation-robust shrinkage method
排序惩罚估计量：相关性稳健收缩方法的推断
Variable correlations pose significant challenges for various LASSO-type shrinkage methods in big-data modeling. This paper presents a comprehensive framework for a correlation-robust shrinkage estimator, enhancing both the theoretical and practical aspects of high-dimensional estimation. We break down the penalty term into a “shrinkage” term and a “grouping” term, illustrating its distinctive properties in clustering highly correlated variables. We establish the…