Empirical Processes in Survey Sampling with (Conditional) Poisson Designs
研究了调查数据中经验过程的渐近性质，在泊松或拒绝抽样设计下建立了函数中心极限定理，适用于非均匀包含概率的抽样设计，并应用于哈达玛可微泛函。
Abstract It is the main purpose of this paper to study the asymptotics of certain variants of the empirical process in the context of survey data. Precisely, Functional Central Limit Theorems are established under usual conditions when the sample is drawn from a Poisson or a rejective sampling design. The framework we develop encompasses sampling designs with non‐uniform first order inclusion probabilities, which can be chosen so as to optimize estimation accuracy. Applications to Hadamard differentiable functionals are considered.