1·An unbiased estimator can be acquired through high order moments of received data.
利用基带数据的高阶矩特性，可以获得渐近无偏估计。
2·In the present paper, We give the necessary and sufficient conditions for which the minimum variance linear unbiased estimator reduces to the least square in multivariate linear models.
本文讨论回归方程组系数的估计，给出最小二乘估计是有效估计的条件。
3·Then, we studied a few of properties of negative binomial distribution and the uniformly unbiased estimator of the parameter, and it's biological significances were explained in Epidemiology.
给出了负二项分布的分解定理，进一步研究了负二项分布的有关性质及参数的无偏一致估计，以及在流行病学该分布的生物学意义。
4·Is it possible for an estimator to be unbiased but inconsistent?
是否有可能(一个估计量)是无偏却不一致的？
5·While not all useful estimators are unbiased, virtually all economists agree that consistency is a minimal requirement for an estimator.
虽然并不是所有的有用的估计量是无偏的，但是，一致性则是经济学家对估计量的最低要求。
6·When the estimator is unbiased, the numerical estimate is frequently also called unbiased.
当估计量无偏时， 数字估计值也常叫做无偏的。
7·The maximum likelihood estimator for population average treatment effect is proved to be consistent, unbiased and asymptotically normal.
并且证明了在正态分布的假设下，该总体平均因果效应的极大似然估计是相合无偏且渐近正态的。
8·Under the normal distribution, the maximum likelihood estimator for the population parameter is proved to be unbiased and asymptotically normal.
证明了此统计量是渐近正态的，并利用蒙特卡罗方法对统计量的渐进分布做了统计模拟。