Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise

@article{Romano2020DetectingAC,
  title={Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise},
  author={G. Romano and Guillem Rigaill and V. Runge and P. Fearnhead},
  journal={arXiv: Methodology},
  year={2020}
}
Whilst there are a plethora of algorithms for detecting changes in mean in univariate time-series, almost all struggle in real applications where there is autocorrelated noise or where the mean fluctuates locally between the abrupt changes that one wishes to detect. In these cases, default implementations, which are often based on assumptions of a constant mean between changes and independent noise, can lead to substantial over-estimation of the number of changes. We propose a principled… Expand
3 Citations

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