TransitionsInTimeseries.jl: A performant, extensible and reliable software for reproducible detection and prediction of transitions in timeseries

Julia Python Submitted 23 February 2024Published 13 July 2024
Review

Editor: @lrnv (all papers)
Reviewers: @felixcremer (all reviews), @sgeorge91 (all reviews)

Authors

Jan Swierczek-Jereczek (0000-0003-2213-0423), George Datseris (0000-0002-6427-2385)

Citation

Swierczek-Jereczek et al., (2024). TransitionsInTimeseries.jl: A performant, extensible and reliable software for reproducible detection and prediction of transitions in timeseries. Journal of Open Source Software, 9(99), 6464, https://doi.org/10.21105/joss.06464

@article{Swierczek-Jereczek2024, doi = {10.21105/joss.06464}, url = {https://doi.org/10.21105/joss.06464}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {99}, pages = {6464}, author = {Jan Swierczek-Jereczek and George Datseris}, title = {TransitionsInTimeseries.jl: A performant, extensible and reliable software for reproducible detection and prediction of transitions in timeseries}, journal = {Journal of Open Source Software} }
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nonlinear dynamics timeseries analysis change point detection resilience loss critical slowing down early warning signals

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ISSN 2475-9066