Package: flexsdm
Type: Package
Title: Flexible Species Distribution Modeling Workflow
Version: 1.4.2
Authors@R: c(person(given = "Santiago J.E.", family = "Velazco", role = c("aut", "cre"),
           email = "sjevelazco@gmail.com",
           comment = c(ORCID = "0000-0002-7527-0967")),
           person(given = "Brooke", family = "Rose", role = c("aut"),
           email = "mrose048@ucr.edu",
           comment = c(ORCID = "0000-0001-5269-3759")),
           person(given = "André F.A.", family = "Andrade", role = c("aut"),
           email = "andrefaandrade@gmail.com",
           comment = c(ORCID = "0000-0002-6134-3176")),
           person(given = "Ignacio", family = "Minoli", role = c("aut"),
           email = "minolicnp@gmail.com",
           comment = c(ORCID = "0000-0002-6039-6962")),
           person(given = "Janet", family = "Franklin", role = c("aut"),
           email = "jfrankl@ucr.edu",
           comment = c(ORCID = "0000-0003-0314-4598")))
Maintainer: Santiago J.E. Velazco <sjevelazco@gmail.com>
URL: https://sjevelazco.github.io/flexsdm/,
        https://github.com/sjevelazco/flexsdm
BugReports: https://github.com/sjevelazco/flexsdm/issues
Depends: R (>= 3.5.0)
Imports: doParallel, dplyr, foreach, gbm, grDevices, kernlab, maxnet,
        mgcv, nnet, randomForest, spThin, terra (>= 1.5-21), methods,
        utils, ggplot2, patchwork, Rcpp
Description: Provides a flexible and comprehensive workflow for species
        distribution modeling, from data preparation (occurrence
        filtering, calibration areas, pseudo-absence and background
        sampling, data partitioning, and collinearity reduction) to
        model fitting, tuning, evaluation, prediction, ensemble
        modeling, and post-processing. The package is described in
        Velazco et al. (2022) <doi:10.1111/2041-210X.13874>.
        Implemented methods include the Shape metric to measure model
        extrapolation of Velazco et al. (2023)
        <doi:10.1111/ecog.06992>, ensembles of small models of Breiner
        et al. (2015) <doi:10.1111/2041-210X.12403> and Breiner et al.
        (2018) <doi:10.1111/2041-210X.12957>, Gaussian process models
        of Golding and Purse (2016) <doi:10.1111/2041-210X.12523>, and
        occurrence-based constraints for post-processing predictions of
        Mendes et al. (2020) <doi:10.1016/j.ecolmodel.2020.109180>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: covr, fs, knitr, rmarkdown, testthat (>= 3.0.0), tibble,
        tidyr
VignetteBuilder: knitr
Config/testthat/edition: 3
LinkingTo: Rcpp
Config/roxygen2/version: 8.1.0
NeedsCompilation: yes
Packaged: 2026-10-24 11:27:38 UTC; root
Author: Santiago J.E. Velazco [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-7527-0967>), Brooke Rose [aut]
        (ORCID: <https://orcid.org/0000-0001-5269-3759>), André F.A.
        Andrade [aut] (ORCID: <https://orcid.org/0000-0002-6134-3176>),
        Ignacio Minoli [aut] (ORCID:
        <https://orcid.org/0000-0002-6039-6962>), Janet Franklin [aut]
        (ORCID: <https://orcid.org/0000-0003-0314-4598>)
Repository: https://cran.r-universe.dev
Date/Publication: 2026-10-24 11:17:53 UTC
RemoteUrl: https://github.com/cran/flexsdm
RemoteRef: HEAD
RemoteSha: 76614d412b93c55243bf0068962ff1f91adbcf8d