Rank-based conformal scores make changepoint localization sets finite-sample valid for any frozen weights and exactly invariant to monotone data transforms, transferring certified set lengths across the entire monotone orbit.
Segmentation and estimation of change-point models: False positive control and confidence regions.The Annals of Statistics, 48:1615– 1647, 2020
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ARC: Augmented-Rank Conformalization for Changepoint Localization --- Finite-Sample Validity and Distribution-Robust Efficiency
Rank-based conformal scores make changepoint localization sets finite-sample valid for any frozen weights and exactly invariant to monotone data transforms, transferring certified set lengths across the entire monotone orbit.