ASYMPTOTIC MINIMAX ESTIMATION IN SEMIPARAMETRIC MODELS

We give several conditions on the estimator of efficient score function for estimating the parametric component of semiparametric models. A semiparametric version of the one-step MLE using an estimator of efficient score function which fulfills the conditions is shown to converge to the normal distribution with minimum variance locally uniformly over a fairly large neighborhood around the assumed semiparametric model. Consequently, it is shown to be asymptotically minimax with bounded subconvex loss functions. A few examples are also considered.