Statistical Matching Analysis for Complex Survey Data With Applications
研究了如何从边缘分布样本估计联合分布，提出了匹配误差概念并给出上界，通过修正条件独立假设构造估计量，用模拟和真实案例验证方法。
The goal of statistical matching is the estimation of a joint distribution having observed only samples from its marginals. The lack of joint observations on the variables of interest is the reason of uncertainty about the joint population distribution function. In the present article, the notion of matching error is introduced, and upper-bounded via an appropriate measure of uncertainty. Then, an estimate of the distribution function for the variables not jointly observed is constructed on the basis of a modification of the conditional independence assumption in the presence of logical constraints. The corresponding measure of uncertainty is estimated via sample data. Finally, a simulation study is performed, and an application to a real case is provided. Supplementary materials for this article are available online.