Robust shift detection in time-varying autoregressive processes

Abstract

Tests for shift detection in locally-stationary autoregressive time series are constructed which resist contamination by a substantial amount of outliers. Tests based on a comparison of local medians standardized by a highly robust estimate of the variability show reliable performance in a broad variety of situations if the thresholds are adjusted for possible autocorrelations.