EWSmethods
Forecasting Tipping Points at the Community Level
Rolling and expanding window approaches to assessing abundance based early warning signals, non-equilibrium resilience measures, and machine learning. See Dakos et al. (2012) doi:10.1371/journal.pone.0041010, Deb et al. (2022) doi:10.1098/rsos.211475, Drake and Griffen (2010) doi:10.1038/nature09389, Ushio et al. (2018) doi:10.1038/nature25504 and Weinans et al. (2021) doi:10.1038/s41598-021-87839-y for methodological details. Graphical presentation of the outputs are also provided for clear and publishable figures. Visit the 'EWSmethods' website for more information, and tutorials.
- Version1.3.1
- R version≥ 4.4
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- EWSmethods citation info
- Last release05/15/2024
Documentation
Team
Duncan O'Brien
Smita Deb
Sahil Sidheekh
Show author detailsRolesAuthorNarayanan Krishnan
Show author detailsRolesAuthorPartha Dutta
Christopher Clements
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