Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)

06/23/2020

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by   Solt Kovács, et al.

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In this discussion, we compare the choice of seeded intervals and that of random intervals for change point segmentation from practical, statistical and computational perspectives. Furthermore, we investigate a novel estimator of the noise level, which improves many existing model selection procedures (including the steepest drop to low levels), particularly for challenging frequent change point scenarios with low signal-to-noise ratios.