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

@article{Rice2022ConsistencyOB,
  title={Consistency of binary segmentation for multiple change-point estimation with functional data},
  author={Gregory Rice and Chi Zhang},
  journal={Statistics \& Probability Letters},
  year={2022}
}
  • G. Rice, Chi Zhang
  • Published 31 December 2019
  • Mathematics
  • Statistics & Probability Letters
Scalable multiple changepoint detection for functional data sequences
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The Multiple Changepoint Isolation method for detecting multiple changes in the mean and covariance of a functional process is proposed and demonstrated on a large time series of water vapor mixing ratio profiles from atmospheric emitted radiance interferometer measurements.
Weighted-Graph-Based Change Point Detection
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The null limiting distribution is derived, accurate analytic approximations to control type I error are provided, and theoretical guarantees on the power consistency under contiguous alternatives for the one change point setting are established, as well as the minimax localization rate.
Bayesian Changepoint Estimation for Spatially Indexed Functional Time Series (preprint)/ en
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