摘要
Convergence rates of empirical Bayes(EB) estimators w-r-t the squared efror loss are con sidered in discrete exponential families. It is shown that a rate O(n^(-1)) is not possible for any EB estimator,even though the parameter space is bounded. Namely, it is proved that the discrete similar of one conjecture of Singh (for Lebesgue-exponential families) is correct.
Convergence rates of empirical Bayes（EB） estimators w-r-t the squared efror loss are con sidered in discrete exponential families. It is shown that a rate O(n<sup>-1</sup>) is not possible for any EB estimator,even though the parameter space is bounded. Namely, it is proved that the discrete similar of one conjecture of Singh （for Lebesgue-exponential families） is correct.
