分组数据下参数极大似然估计渐近有效性

ASYMPTOTICAL EFFICIENCY OF MLE WITH GROUPED DATA

当数据为分组型时，本文证明了一般分布的参数的极大似然估计具有指数收敛速 度，并具有Ｂａｈａｄｕｒ渐近有效性．

In this paper, the convergence rate of the MLE with grouped data is discussed. Under some mild conditions, it is shown that the MLE converges to the true parameter at an exponential rate. Furthermore, the MLE is Bahadur asymptotically efficient, i.e. it has the best exponential rate.