标题： 分析海量数据的分布式顺序方法 显示英文标题

标题： Distributed sequential method for analyzing massive data

摘要： 为了分析包含长变量的非常大的数据集，我们采用了顺序估计的思想，并提出了一种并行分而治之的方法。 我们分别进行几种常规的顺序估计程序，并在保持所需统计特性的同时适当整合其结果。 此外，利用统计实验设计中的一个准则，我们采用自适应样本选择以及自适应收缩估计方法，以同时加速估计过程并识别有效变量。 我们通过理论论证和合成数据集得出的数值结果验证了我们方法的有效性。 随后，我们将所提出的方法应用于三个真实数据集，其中包括家电能耗和颗粒物浓度相关的数据集。 显示英文摘要

摘要： To analyse a very large data set containing lengthy variables, we adopt a sequential estimation idea and propose a parallel divide-and-conquer method. We conduct several conventional sequential estimation procedures separately, and properly integrate their results while maintaining the desired statistical properties. Additionally, using a criterion from the statistical experiment design, we adopt an adaptive sample selection, together with an adaptive shrinkage estimation method, to simultaneously accelerate the estimation procedure and identify the effective variables. We confirm the cogency of our methods through theoretical justifications and numerical results derived from synthesized data sets. We then apply the proposed method to three real data sets, including those pertaining to appliance energy use and particulate matter concentration.