Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit
刻画 SLOPE 的权衡:变分视角与 Donoho–Tanner 极限
Sorted ℓ1 regularization has been incorporated into many methods for solving high-dimensional statistical estimation problems, including the SLOPE estimator in linear regression. In this paper, we study how this relatively new regularization technique improves variable selection by characterizing the optimal SLOPE trade-off between the false discovery proportion (FDP) and true positive proportion (TPP) or, equivalently, between measures of type I error and power. Assuming a…