Basic functions for plotting 2D and 3D views of a sphere, by default the Earth with its major coastline, and additional lines and points.

Generalized LassO applied to knot selection in multivariate B-splinE Regression (GLOBER) implements a novel approach for estimating functions in a multivariate nonparametric regression model based on an adaptive knot selection for B-splines using the Generalized Lasso. For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, C. (2023), <arXiv:2306.00686>.

Tools for the generalized logistic distribution (Type I,
             also known as skew-logistic distribution), encompassing
	     basic distribution functions (p, q, d, r, score), maximum
	     likelihood estimation, and structural change methods.

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.

Add glossaries to markdown and quarto documents by tagging individual words. Definitions can be provided inline or in a separate file.

Read examples with interlinear glosses from files
    or from text and print them in a way compatible with both
    Latex and HTML outputs.

Streamlined workflows for geolinguistic analysis, including:
    accessing global linguistic and cultural databases, data import, data
    entry, data cleaning, data exploration, mapping, visualization and
    export.