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    Narrowest Significance Pursuit: Inference for Multiple Change-Points in Linear Models by Piotr Fryzlewicz (3643930)

    Published 2023
    “…<p>We propose Narrowest Significance Pursuit (NSP), a general and flexible methodology for automatically detecting localized regions in data sequences which each must contain a change-point (understood as an abrupt change in the parameters of an underlying linear model), at a prescribed global significance level. …”
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