Vector auto-regression

Multiple Change Points Detection in Low Rank and Sparse High Dimensional Vector Autoregressive Models

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 …