Ld. Brown et Mg. Low, A CONSTRAINED RISK INEQUALITY WITH APPLICATIONS TO NONPARAMETRIC FUNCTIONAL ESTIMATION, Annals of statistics, 24(6), 1996, pp. 2524-2535
A general constrained minimum risk inequality is derived. Given two de
nsities f(theta) and f(0) we find a lower bound for the risk at the po
int theta given an upper bound for the risk at the point 0. The inequa
lity sheds new light on superefficient estimators in the normal locati
on problem and also on an adaptive estimation problem arising in nonpa
rametric functional estimation.