Minimax Estimation of Proportions Under Random Sample Size
研究了样本量为辅助统计量时多元超几何分布参数的最小最大估计，给出了平方误差损失下的估计量，并证明固定样本量下的经典估计量在随机样本量下不可容许。
Abstract We study the problem of how to estimate the parameters of a multivariate hypergeometric distribution when the sample size n is assumed to be an ancillary statistic. The minimax estimator for squared error loss is given. This estimator differs from the well-known minimax estimator for fixed n. Furthermore, that classical estimator is shown to be not even admissible when n is random.