  We discuss Fryzlewicz's (2020) 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.
