Changepoint Detection in the Presence of Outliers¶
Fearnhead, P., & Rigaill, G. (2019). Changepoint Detection in the Presence of Outliers. Journal of the American Statistical Association, 114(525), 169-183.
Cited by¶
1 citation across 1 artifact.
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Mechanisms¶
- Change-Point and Regime-Switching Model
- It can hallucinate breaks in noisy or heavy-tailed data, where any excursion looks like a shift, and it readily confounds a true regime change with a slow trend or a single outlier; retrospective change-point dates are themselves uncertain and routinely over-trusted.
This sourceShows that conventional change-point methods can infer spurious additional changes when data contain outliers or heavy-tailed noise.
- It can hallucinate breaks in noisy or heavy-tailed data, where any excursion looks like a shift, and it readily confounds a true regime change with a slow trend or a single outlier; retrospective change-point dates are themselves uncertain and routinely over-trusted.
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