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《流式纵向数据的统计推断》讨论回复AI 解读

We thank the editorial board for organizing this discussion and giving us the opportunity to explore experts’ perspectives on our work. We sincerely appreciate the discussants for their insightful contributions, which have raised many important points and provided suggestions for potential improvements and generalizations of our proposed method. In this rejoinder, we primarily focus on three important aspects raised by the discussants: (i) the role of the weighting parameter…

流式纵向数据的统计推断AI 解读

Summary Modern longitudinal data, for example from wearable devices, may consist of measurements of biological signals on a fixed set of participants at a diverging number of time-points. Traditional statistical methods are not equipped to handle the computational burden of repeatedly analysing the cumulatively growing dataset each time new data are collected. We propose a new estimation and inference framework for dynamic updating of point estimates and their standard…