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変化点検出(PELT)×逐次分析(群逐次計画)×
分野統計学統計学
系統Machine learningHypothesis test
提唱年20121977
提唱者Killick, Fearnhead & EckleyP. C. O'Brien & T. R. Fleming; P. C. Pocock
種類Sequential segmentation algorithmSequential / adaptive hypothesis test
原典Killick, R., Fearnhead, P., & Eckley, I. A. (2012). Optimal detection of changepoints with a linear computational cost. Journal of the American Statistical Association, 107(500), 1590–1598. DOI ↗O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556. DOI ↗
別名Structural Break Detection, Breakpoint Analysis, Regime Change Detection, Değişim Noktası Tespitisequential testing, group sequential design, interim analysis, Sıralı Analiz (Sequential Testing / Group Sequential Design)
関連25
概要Change-Point Detection identifies time points at which the statistical properties of a sequence — such as mean, variance, or distribution — shift abruptly. The Pruned Exact Linear Time (PELT) algorithm, introduced by Killick, Fearnhead, and Eckley (2012), solves the penalized segmentation problem exactly while achieving linear expected computational cost, making it practical for long time series encountered in genomics, finance, climatology, and signal processing.Sequential analysis is a framework for conducting hypothesis tests with pre-planned interim looks at accumulating data, allowing a study to stop early for efficacy or futility while controlling the overall Type I error rate. The group sequential approach was formalised by Pocock (1977) and O'Brien and Fleming (1979), and remains the standard for confirmatory clinical trials and rigorous A/B experiments.
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ScholarGate手法を比較: Change-Point Detection · Sequential Analysis. 2026-06-15に以下より取得 https://scholargate.app/ja/compare