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EWSmethods  

Forecasting Tipping Points at the Community Level
View on CRAN: Click here


Download and install EWSmethods package within the R console
Install from CRAN:
install.packages("EWSmethods")

Install from Github:
library("remotes")
install_github("cran/EWSmethods")

Install by package version:
library("remotes")
install_version("EWSmethods", "1.3.1")



Attach the package and use:
library("EWSmethods")
Maintained by
Duncan O'Brien
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-04-25
Latest Update: 2024-01-11
Description:
Rolling and expanding window approaches to assessing abundance based early warning signals, non-equilibrium resilience measures, and machine learning. See Dakos et al. (2012) , Deb et al. (2022) , Drake and Griffen (2010) , Ushio et al. (2018) and Weinans et al. (2021) 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.
How to cite:
Duncan O'Brien (2023). EWSmethods: Forecasting Tipping Points at the Community Level. R package version 1.3.1, https://cran.r-project.org/web/packages/EWSmethods. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.1.2 (2023-04-25 20:10), 1.2.1 (2023-11-07 20:50), 1.2.4 (2024-01-09 20:50), 1.2.5 (2024-01-11 09:50)
Other packages that cited EWSmethods R package
View EWSmethods citation profile
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Complete documentation for EWSmethods
Functions, R codes and Examples using the EWSmethods R package
Full EWSmethods package functions and examples
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