Makes easier the creation of R package or research compendium 
    (i.e. a predefined files/folders structure) so that users can focus on the 
    code/analysis instead of wasting time organizing files. A full 
    ready-to-work structure is set up with some additional features: version 
    control, remote repository creation, CI/CD configuration (check package 
    integrity under several OS, test code with 'testthat', and build and deploy 
    website using 'pkgdown'). This package heavily relies on the R packages 
    'devtools' and 'usethis' and follows recommendations made by Wickham H. 
    (2015) <ISBN:9781491910597> and Marwick B. et al. (2018) 
    <doi:10.7287/peerj.preprints.3192v2>.

Minimal and lightweight configuration tool that provides basic support for 'YAML' configuration files without requiring additional package dependencies. It offers a simple method for loading and parsing configuration settings, making it ideal for quick prototypes and lightweight projects.

Configuration management using files (YAML, JSON, INI, TXT),
  JSON strings, and command line arguments. Command line arguments
  can be used to override configuration. Period-separated command line
  flags are parsed as hierarchical lists. Environment variables, R global variables,
  and configuration values can be substituted.

Solve some conic related problems (intersection of conics with lines and conics, arc length of an ellipse, polar lines, etc.).

'TROLL' is coded in C++ and it typically simulates hundreds of
    thousands of individuals over hundreds of years. The 'rcontroll' R package 
    is a wrapper of 'TROLL'. 'rcontroll' includes functions that generate inputs 
    for simulations and run simulations. Finally, it is possible to analyse 
    the 'TROLL' outputs through tables, figures, and maps taking advantage of 
    other R visualisation packages. 'rcontroll' also offers the possibility to 
    generate a virtual LiDAR point cloud that corresponds to a snapshot of 
    the simulated forest.