We study the problem of detecting and locating change points in high-dimensional Vector Autoregressive (VAR) models, whose transition matrices exhibit low rank plus sparse structure. We first address the problem of detecting a single change point …
Identifying change/break points in multivariate time series represents a canonical problem in signal processing, due to numerous applications related to anomaly detection problems. The underlying detection methodology heavily depends on the nature of …