标题： 数据增强与参数扩展下的统计推断 显示英文标题

标题： Statistical Inference with Data Augmentation and Parameter Expansion

摘要： 统计实用主义接纳统计推断中所有有效的方法。 在此使用收集数据的扩充来从一大类非代表性总体的单元中获得具有代表性的总体信息。 概率模型的参数扩展被证明可以降低简单假设检验中误差概率总和的上限，并提出了一种度量 R 来衡量激活充分统计量中的附加组件（或组件）的效果。 显示英文摘要

摘要： Statistical pragmatism embraces all efficient methods in statistical inference. Augmentation of the collected data is used herein to obtain representative population information from a large class of non-representative population's units. Parameter expansion of a probability model is shown to reduce the upper bound on the sum of error probabilities for a test of simple hypotheses, and a measure, R, is proposed for the effect of activating additional component(s) in the sufficient statistic.