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

arXiv: https://arxiv.org/abs/2006.12806 · HTML: https://mlsanity.com/paper/2006.12806/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Random Forests for Change Point Detection](https://mlsanity.com/paper/2205.04997/) (2022)

## Abstract (arXiv)

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.