3 papers
stat.ME2025
Sequential Change-point Detection for Compositional Time Series with Exogenous Variables
Yajun Liu, Beth Andrews
Sequential change-point detection for time series enables us to sequentially check the hypothesis that the model still holds as more and more data are observed. It is widely used i…
stat.ME2025
Sequential Change-point Detection for Binomial Time Series
Yajun Liu, Beth Andrews
A binomial time series describes binary behaviors of individuals within a group, which depend on group behaviors in the past. Binomial time series data is widely applied in fields…
stat.ME2025
Nonparametric Sequential Change-point Detection on High Order Compositional Time Series Models with Exogenous Variables
Yajun Liu, Beth Andrews
Sequential change-point detection for time series is widely used in data monitoring in practice. In this work, we focus on sequential change-point detection on high-order compositi…