Bayesian Online Change Point Detection for Baseline Shifts. (arXiv:2201.02325v1 [stat.ML])

In time series data analysis, detecting change points on a real-time basis
(online) is of great interest in many areas, such as finance, environmental
monitoring, and medicine. One promising means to achieve this is the Bayesian
online change point detection (BOCPD) algorithm, which has been successfully
adopted in particular cases in which the time series of interest has a fixed
baseline. However, we have found that the algorithm struggles when the baseline
irreversibly shifts from its initial state. This is …

arxiv bayesian change detection ml