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有限总体规模序贯估计中最大似然估计量的不可容许性AI 解读

For the sequential estimation of the size of a finite population, the maximum likelihood estimator is a commonly used estimator but has no explicit expression. In this paper, it is shown that the maximum likelihood estimator is inadmissible. An estimator which is simple in form and dominates the maximum likelihood estimator asymptotically is proposed.

样本均值函数的 Edgeworth 展开AI 解读

Many important statistics can be written as functions of sample means of vector variables. A fundamental contribution to the Edgeworth expansion for functions of sample means was made by Bhattacharya and Ghosh. In their work the crucial Cramer $c$-condition is assumed on the joint distribution of all the components of the vector variable. However, in many practical situations, only one or a few of the components satisfy (conditionally) this condition while the rest do not…

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