NOMAD unifies shrinkage and thresholding estimation by minimizing a data-driven approximate risk criterion derived via Stein's identity and Tweedie's formula, recovering James-Stein and lasso as special cases.
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Approximate Risk Minimization Over Shrinking-Thresholding Rules in Normal Mean Estimation
NOMAD unifies shrinkage and thresholding estimation by minimizing a data-driven approximate risk criterion derived via Stein's identity and Tweedie's formula, recovering James-Stein and lasso as special cases.