Consistency of binary segmentation for multiple change-point estimation with functional data

Abstract

For sequentially observed functional data exhibiting multiple change points in the mean function, we establish consistency results for the estimated number and locations of the change points based on the norm of functional CUSUM processes and standard binary segmentation. Our main results are established under conditions allowing for general serial dependence structures in the observations, and low moments.