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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3.3 |
rolling source/ R- | EWSmethods_1.3.3.tar.gz |
3.0 MiB |
1.3.3 |
latest source/ R- | EWSmethods_1.3.3.tar.gz |
3.0 MiB |
1.3.3 |
2026-04-23 source/ R- | EWSmethods_1.3.3.tar.gz |
3.0 MiB |
1.3.3 |
2026-04-09 windows/windows R-4.5 | EWSmethods_1.3.3.zip |
2.9 MiB |