A Multiprocess State Space Model with Feedback and Switching for Patterns of Clinical Measurements Associated with COVID-19
用于COVID-19相关临床测量的反馈切换多过程状态空间模型
Clinical measurements, such as body temperature, are often collected over time to monitor an individual's underlying health condition. These measurements exhibit complex temporal dynamics, necessitating sophisticated statistical models to capture patterns and detect deviations. We propose a novel multiprocess state space model with feedback and switching mechanisms to analyze the dynamics of clinical measurements. This model captures the evolution of time series through…