A log-linear time algorithm for constrained changepoint detection

Hocking, Toby Dylan and Rigaill, Guillem and Fearnhead, Paul and Bourque, Guillaume (2017) A log-linear time algorithm for constrained changepoint detection. arXiv.

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Changepoint detection is a central problem in time series and genomic data. For some applications, it is natural to impose constraints on the directions of changes. One example is ChIP-seq data, for which adding an up-down constraint improves peak detection accuracy, but makes the optimization problem more complicated. We show how a recently proposed functional pruning technique can be adapted to solve such constrained changepoint detection problems. This leads to a new algorithm which can solve problems with arbitrary affine constraints on adjacent segment means, and which has empirical time complexity that is log-linear in the amount of data. This algorithm achieves state-of-the-art accuracy in a benchmark of several genomic data sets, and is orders of magnitude faster than existing algorithms that have similar accuracy. Our implementation is available as the PeakSegPDPA function in the coseg R package, https://github.com/tdhock/coseg

Item Type: Journal Article
Journal or Publication Title: arXiv
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 85707
Deposited By: ep_importer_pure
Deposited On: 24 Mar 2017 15:34
Refereed?: No
Published?: Published
Last Modified: 27 Feb 2020 03:40
URI: https://eprints.lancs.ac.uk/id/eprint/85707

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