Long signal change-point detection

Abstract : The detection of change-points in a spatially or time ordered data sequence is an important problem in many fields such as genetics and finance. We derive the asymptotic distribution of a statistic recently suggested for detecting change-points. Simulation of its estimated limit distribution leads to a new and computationally efficient change-point detection algorithm, which can be used on very long signals. We assess the algorithm via simulations and on previously benchmarked real-world data sets.
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Article dans une revue
Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2016, 〈10.1214/16-EJS1164〉
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https://hal.inria.fr/hal-01140119
Contributeur : Kevin Bleakley <>
Soumis le : lundi 28 septembre 2015 - 13:28:54
Dernière modification le : mercredi 21 mars 2018 - 18:56:49
Document(s) archivé(s) le : mercredi 26 avril 2017 - 18:32:19

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Gérard Biau, Kevin Bleakley, David Mason. Long signal change-point detection. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2016, 〈10.1214/16-EJS1164〉. 〈hal-01140119v2〉

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