Functions for constructing Transformed and Relative Lorenz curves with survey sampling weights. Given a variable of interest measured in two groups with scaled survey weights so that their hypothetical populations are of equal size, tlorenz() computes the proportion of members of the group with smaller values (ordered from smallest to largest) needed for their sum to match the sum of the top qth percentile of the group with higher values. rlorenz() shows the fraction of the total value of the group with larger values held by the pth percentile of those in the group with smaller values. Fd() is a survey weighted cumulative distribution function and Eps() is a survey weighted inverse cdf used in rlorenz(). Ramos, Graubard, and Gastwirth (2025) <doi:10.1093/jrsssa/qnaf044>.

A user-friendly 'shiny' application for Bayesian machine
    learning analysis of marine species distributions. GLOSSA (Global
    Ocean Species Spatio-temporal 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. Optionally, pseudo-absences can
    be generated within the environmental space using the external package
    'flexsdm' (not on CRAN), which can be downloaded from
    <https://github.com/sjevelazco/flexsdm>; this functionality is used
    conditionally when available and all core features work without it.

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