Many relevant applications in the environmental and socioeconomic 
    sciences use areal data, such as biodiversity checklists, agricultural statistics, 
    or socioeconomic surveys. For applications that surpass the spatial, temporal or 
    thematic scope of any single data source, data must be integrated from several 
    heterogeneous sources. Inconsistent concepts, definitions, or messy data tables 
    make this a tedious and error-prone process. 'arealDB' tackles those problems and 
    helps the user to integrate a harmonised databases of areal data. Read the paper
    at Ehrmann, Seppelt & Meyer (2020) <doi:10.1016/j.envsoft.2020.104799>.

Plot stacked areas and confidence bands as filled polygons, or add
  polygons to existing plots. A variety of input formats are supported,
  including vectors, matrices, data frames, formulas, etc.

Reads Arena <https://www.arenasimulation.com/> CSV output files and generates nice tables and plots. The package contains a Shiny App that can be used to interactively visualize Arena's results.

Generates data for challenging machine learning models in 'Arena'
    <https://arena.drwhy.ai> - an interactive web application. You can start
    the server with XAI (Explainable Artificial Intelligence) plots to be
    generated on-demand or precalculate and auto-upload data file beside
    shareable 'Arena' URL.

Adversarial random forests (ARFs) recursively partition data into 
    fully factorized leaves, where features are jointly independent. The 
    procedure is iterative, with alternating rounds of generation and 
    discrimination. Data becomes increasingly realistic at each round, until 
    original and synthetic samples can no longer be reliably distinguished. 
    This is useful for several unsupervised learning tasks, such as density
    estimation and data synthesis. Methods for both are implemented in this
    package. ARFs naturally handle unstructured data with mixed continuous and 
    categorical covariates. They inherit many of the benefits of random forests, 
    including speed, flexibility, and solid performance with default parameters. 
    For details, see Watson et al. (2022) <arXiv:2205.09435>.