Abstract
AbstractA general lower bound of minimax risk for absolute‐error loss is given in terms of the Hellinger modulus of the estimation problem. The main results are applicable to various parametric, semi‐parametric and nonparametric problems. Two examples of parametric estimation problems and two examples of density estimation problems are given. In all of these examples, the general lower bound achieves the convergence rates of minimax risk.
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