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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https://hal.inria.fr/hal-01140119
Contributor : Kevin Bleakley <>
Submitted on : Monday, September 28, 2015 - 1:28:54 PM
Last modification on : Friday, May 24, 2019 - 5:31:02 PM
Long-term archiving on : Wednesday, April 26, 2017 - 6:32:19 PM

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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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