Bootstrapping Empirical Functions
本文建立了加权经验过程和分位过程自举理论的完整框架，提出一套通用技术来证明自举法构建统计函数置信带的渐近有效性，并展示了其在多种具体函数上的应用。
We develop the complete bootstrapped parallel to the asymptotic theory of weighted empirical and quantile processes. Utilizing this parallel theory, we present a general body of techniques to establish the asymptotic validity of the bootstrap method of constructing confidence bands for statistical functions. These techniques are demonstrated to be applicable to the construction of asymptotic bootstrap confidence bands for a variety of concrete functions.