论文标题
种子间隔和变化点检测中的噪声水平估计：Fryzlewicz的讨论（2020）
Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
论文作者
论文摘要
在此讨论中，我们比较了种子间隔的选择以及从实际，统计和计算的角度进行变化点分割的随机间隔的选择。此外，我们研究了噪声水平的新型估计器，该估计值改善了许多现有的模型选择程序（包括最陡峭的下降到低水平），尤其是对于具有低信噪比比率低的频繁变化点方案而言。
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.
