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, thus establishing its validity. 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. To finish, we briefly assess this new algorithm on one- and multi-dimensional data.
Citation
Gérard Biau. Kevin Bleakley. David M. Mason. "Long signal change-point detection." Electron. J. Statist. 10 (2) 2097 - 2123, 2016. https://doi.org/10.1214/16-EJS1164
Information