Package: EWSmethods 1.3.3.9000

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.

Authors:Duncan O'Brien [aut, cre, cph], Smita Deb [aut], Sahil Sidheekh [aut], Narayanan Krishnan [aut], Partha Dutta [aut], Christopher Clements [aut]

EWSmethods_1.3.3.9000.tar.gz
EWSmethods_1.3.3.9000.zip(r-4.7)EWSmethods_1.3.3.9000.zip(r-4.6)EWSmethods_1.3.3.9000.zip(r-4.5)
EWSmethods_1.3.3.9000.tgz(r-4.6-any)EWSmethods_1.3.3.9000.tgz(r-4.5-any)
EWSmethods_1.3.3.9000.tar.gz(r-4.7-any)EWSmethods_1.3.3.9000.tar.gz(r-4.6-any)
EWSmethods_1.3.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
EWSmethods/json (API)
NEWS

# Install 'EWSmethods' in R:
install.packages('EWSmethods', repos = c('https://duncanobrien.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/duncanobrien/ewsmethods/issues

Pkgdown/docs site:https://duncanobrien.github.io

Datasets:

On CRAN:

Conda:

5.32 score 10 stars 21 scripts 573 downloads 26 exports 52 dependencies

Last updated from:59fded2fef. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK199
source / vignettesOK249
linux-release-x86_64OK188
macos-release-arm64OK177
macos-oldrel-arm64OK221
windows-develOK191
windows-releaseOK149
windows-oldrelOK126
wasm-releaseOK136

Exports:conda_cleandefault_sewsnet_pathdefault_weights_pathdeseason_tsdetrend_tsembed_tsewsnet_finetuneewsnet_initewsnet_predictewsnet_resetFIIIimbalance_gainmulti_smap_jacobianmultiARmultiEWSmultiJImviperm_rollEWSsewsnet_predictsewsnet_resettuneIIuni_smap_jacobianuniARuniEWSuniJI

Dependencies:clicodetoolscolorspacecpp11curleggfarverforeachforecastfracdiffgenericsggplot2gluegridExtragtablegtoolshereinfotheoisobanditeratorsjsonlitelabelinglatticelifecyclelmtestmagrittrmArMASSMatrixmomentsnlmennetpngR6rappdirsRColorBrewerRcppRcppArmadilloRcppThreadRcppTOMLrEDMreticulaterlangrprojrootS7scalestimeDateurcavctrsviridisLitewithrzoo

Performing Early Warning Signal Assessments

Rendered fromews_assessments.Rmdusingknitr::rmarkdownon May 24 2026.

Last update: 2026-03-30
Started: 2022-08-31