Bayesian Sequential Two-Phase Sampling
提出一种序贯两阶段抽样方法，解决传统两阶段抽样无法适用的问题，推导最优及近似最优序贯决策程序，并以鱼类年龄分布推断为例展示其效果。
Abstract We propose a sequential two-phase sample design to accommodate applications where conventional two-phase sampling cannot be used. First, we derive the optimal, the optimal myopic, and several approximate optimal myopic sequential decision procedures for subsampling a first-phase sample. Then we compare our procedure to that of the optimal (nonsequential) conventional two-phase sample design. In our application, the objective is inference about the age distribution of a population of fish using data on covariates (e.g., length, weight) obtained from all members of the first-phase sample and data on age obtained from the fish in the second-phase subsample.