Computational Methods for Measuring the Difference of Empirical Distributions
提出一种简单的计算方法，通过自助法或其他重抽样技术衡量独立经验分布之间的差异，并基于条件估值中的实地测试数据，与其他方法比较了编程复杂度、资源需求和估计精度。
Abstract This paper presents a simple computational method for measuring the difference of independent empirical distributions estimated by bootstrapping or other resampling approaches. Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate.