Type: Package
Package: EWSmethods
Title: Forecasting Tipping Points at the Community Level
Version: 1.3.3.9000
Authors@R: c(
    person(given   = "Duncan",
           family  = "O'Brien",
           email   = "duncan.a.obrien@gmail.com",
           role    = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-3420-5210")),
    person(given   = "Smita",
           family  = "Deb",
           email   = "smita.19maz0004@iitrpr.ac.in",
           role    = "aut",
           comment = c(ORCID = "0000-0001-7037-7055")),
    person(given   = "Sahil",
           family  = "Sidheekh",
           email   = "sahil.sidheekh@outlook.com",
           role    = "aut"),
    person(given   = "Narayanan",
           family  = "Krishnan",
           email   = "ckn@iitpkd.ac.in",
           role    = "aut"),
    person(given   = "Partha",
           family  = "Dutta",
           email   = "parthasharathi@iitrpr.ac.in",
           role    = "aut",
           comment = c(ORCID = "0000-0001-6067-1023")),
    person(given   = "Christopher",
           family  = "Clements",
           email   = "c.clements@bristol.ac.uk",
           role    = "aut",
           comment = c(ORCID = "0000-0001-5677-5401")))
Maintainer: Duncan O'Brien <duncan.a.obrien@gmail.com>
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) <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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: curl, egg, ggplot2, gtools, forecast, foreach, infotheo, mAr,
        moments, rEDM (>= 1.15.0), reticulate, scales
RoxygenNote: 7.3.3
URL: https://github.com/duncanobrien/EWSmethods,
        https://duncanobrien.github.io/EWSmethods/
BugReports: https://github.com/duncanobrien/EWSmethods/issues
Suggests: data.table, devtools, doParallel, knitr, fs, parallel,
        rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 4.4)
Config/testthat/edition: 3
Config/pak/sysreqs: libpng-dev libssl-dev python3
Repository: https://duncanobrien.r-universe.dev
Date/Publication: 2026-03-30 15:50:15 UTC
RemoteUrl: https://github.com/duncanobrien/ewsmethods
RemoteRef: HEAD
RemoteSha: 59fded2fef63f9fc3ec62b62daf7b18408a13d08
NeedsCompilation: no
Packaged: 2026-06-23 06:46:03 UTC; root
Author: Duncan O'Brien [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-3420-5210>),
  Smita Deb [aut] (ORCID: <https://orcid.org/0000-0001-7037-7055>),
  Sahil Sidheekh [aut],
  Narayanan Krishnan [aut],
  Partha Dutta [aut] (ORCID: <https://orcid.org/0000-0001-6067-1023>),
  Christopher Clements [aut] (ORCID:
    <https://orcid.org/0000-0001-5677-5401>)