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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "glossa" in publications use:'
type: software
license: GPL-3.0-only
title: 'glossa: User-Friendly ''shiny'' App for Bayesian Species Distribution Models'
version: 1.0.0
doi: 10.32614/CRAN.package.glossa
abstract: A user-friendly 'shiny' application for Bayesian machine learning analysis
  of marine species distributions. GLOSSA (Global Species Spatiotemporal Analysis)
  uses Bayesian Additive Regression Trees (BART; Chipman, George, and McCulloch (2010)
  <https://doi.org/10.1214/09-AOAS285>) to model species distributions with intuitive
  workflows for data upload, processing, model fitting, and result visualization.
  It supports presence-absence and presence-only data (with pseudo-absence generation),
  spatial thinning, cross-validation, and scenario-based projections. GLOSSA is designed
  to facilitate ecological research by providing easy-to-use tools for analyzing and
  visualizing marine species distributions across different spatial and temporal scales.
authors:
- family-names: Mestre-Tomás
  given-names: Jorge
  email: jorge.mestre.tomas@csic.es
  orcid: https://orcid.org/0000-0002-8983-3417
- family-names: Fuster-Alonso
  given-names: Alba
  orcid: https://orcid.org/0000-0002-7283-291X
repository: https://imares-group.r-universe.dev
repository-code: https://github.com/iMARES-group/glossa
commit: 7207cf041dd5be660f0a427ad91f589f0ddbe72b
url: https://iMARES-group.github.io/glossa/
contact:
- family-names: Mestre-Tomás
  given-names: Jorge
  email: jorge.mestre.tomas@csic.es
  orcid: https://orcid.org/0000-0002-8983-3417