We discuss Fryzlewicz’s paper that proposes WBS2.SDLL approach to detect possibly frequent changes in mean of a series. Our focus is on the potential issues related to the model misspecification. We present some numerical examples such as the self-exciting threshold autoregression and the unit root process, that can be confused as a frequent change-points model.

中文翻译：

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频繁或系统的更改？关于“检测可能频繁变化的点：Wild Binary Segmentation 2和最陡峭的模型选择”的讨论。

我们讨论Fryzlewicz的论文，该论文提出了WBS2.SDLL方法来检测序列均值中可能频繁发生的变化。我们的重点是与模型规格不正确相关的潜在问题。我们提供了一些数值示例，例如自励阈值自回归和单位根过程，它们可以与频繁变化点模型混淆。