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glossa  

User-Friendly 'shiny' App for Bayesian Species Distribution Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("glossa", "1.2.4")



Attach the package and use:
library("glossa")
Maintained by
Jorge Mestre-Tomás
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-15
Latest Update: 2025-08-27
Description:
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) <doi: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.
How to cite:
Jorge Mestre-Tomás (2024). glossa: User-Friendly 'shiny' App for Bayesian Species Distribution Models. R package version 1.2.4, https://cran.r-project.org/web/packages/glossa. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:44), 1.0.0 (2024-10-15 17:10), 1.1.0 (2025-05-28 01:10), 1.2.0 (2025-06-17 10:30), 1.2.1 (2025-06-20 18:20), 1.2.2 (2025-07-15 18:00), 1.2.3 (2025-08-27 15:00)
Other packages that cited glossa R package
View glossa citation profile
Other R packages that glossa depends, imports, suggests or enhances
Complete documentation for glossa
Functions, R codes and Examples using the glossa R package
Full glossa package functions and examples
Downloads during the last 30 days

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