Robust Shift Detection in Time-Varying Autoregressive Processes
DOI:
https://doi.org/10.17713/ajs.v37i1.285Abstract
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.
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