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Optimal Detection of Changepoints With a Linear Computational Cost
R. Killick, P. Fearnhead, I. A. Eckley, 2012. Journal of the American Statistical Association.
Introduces PELT, a changepoint detection algorithm that finds the best number and placement of changepoints in a series at a cost that grows only linearly with its length, under mild conditions.
What it's used for here
Three methods surveys (bioinformatics and signal analysis, emerging methods, inductive methods) cite it for detecting changepoints along the text.
Cited by on this site 3 records
3 methods surveys
SRCSignal processing, mathematics, inductive methods
Cite it
Killick, R., Fearnhead, P., & Eckley, I. A. (2012). Optimal Detection of Changepoints With a Linear Computational Cost. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2012.737745
@article{killick2012optimal,
author = {Killick, R. and Fearnhead, P. and Eckley, I. A.},
title = {Optimal Detection of Changepoints With a Linear Computational Cost},
journal = {Journal of the American Statistical Association},
year = {2012},
doi = {10.1080/01621459.2012.737745},
url = {https://doi.org/10.1080/01621459.2012.737745}
}TY - JOUR TI - Optimal Detection of Changepoints With a Linear Computational Cost AU - Killick, R. AU - Fearnhead, P. AU - Eckley, I. A. PY - 2012 JO - Journal of the American Statistical Association DO - 10.1080/01621459.2012.737745 UR - https://doi.org/10.1080/01621459.2012.737745 ER -
Killick, R. et al.. “Optimal Detection of Changepoints With a Linear Computational Cost.” Journal of the American Statistical Association (2012). https://doi.org/10.1080/01621459.2012.737745.