2015/04/07 by Gérard Biau, Kevin Bleakley, Biau, Gérard +3
Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #FOS: Mathematics #Statistics Theory (math.ST) #math.ST #stat.AP #stat.TH
paper · pdf · doi:10.48550/arxiv.1504.01702
arxiv created 2015/09/30 · arxiv updated 2015/10/01
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.