Approximate Risk Minimization Over Shrinking-Thresholding Rules in Normal Mean Estimation
正态均值估计中收缩阈值规则的近似风险最小化
We develop an approximate risk minimization framework for shrinkage-thresholding estimation in normal mean problems. In the canonical multivariate normal mean model, we introduce a general functional class of estimators that contains classical shrinkage and thresholding behavior, including James-Stein-type and lasso-type rules. We express quadratic risk as a functional over this class, derive optimality conditions for both oracle risk and data-driven approximate risk…