Estimation of Location Difference for Fragmentary Samples
针对相关变量中部分观测缺失的情况，提出一类简单稳健的位置参数差异估计量，证明其一致性、渐近正态性和对异常值不敏感，并通过渐近相对效率比较展示优势。
A class of simple and robust estimators of the difference between location parameters of correlated variables is proposed when some observations on either of the variables are missing. We show that these estimators are consistent, asymptotically normally distributed, and insensitive to outlying observations. Asymptotic relative efficiency comparisons with other known estimators are made to show the advantage of the proposed estimators.