Simulates and evaluates stochastic scenarios of death and lapse events in life reinsurance contracts with profit commissions. The methodology builds on materials published by the Institute of Actuaries of Japan <https://www.actuaries.jp/examin/textbook/pdf/modeling.pdf>. A paper describing the detailed algorithms will be published by the author within a few months after the initial release of this package.

Facilitates modeling species' ecological niches and 
  geographic distributions based on occurrences and environments that 
  have a vertical as well as horizontal component, and projecting models 
  into three-dimensional geographic space. Working in three dimensions is 
  useful in an aquatic context when the organisms one wishes to model can 
  be found across a wide range of depths in the water column. The package
  also contains functions to automatically generate marine training
  model training regions using machine learning, and interpolate and smooth
  patchily sampled environmental rasters using thin plate splines.
  Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) <doi:10.1038/ncomms11484>.
  Nychka D, Furrer R, Paige J, Sain S (2021) <doi:10.5065/D6W957CT>.
  Pateiro-Lopez B, Rodriguez-Casal A (2022) <https://CRAN.R-project.org/package=alphahull>.

Creates visualization plots for 2D projected data including ellipse plots, Voronoi diagram plots, and combined ellipse-Voronoi plots. Designed to visualize class separation in dimensionally reduced data from techniques like principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or others. For more details see Lotsch and Ultsch (2024) <doi:10.1016/j.imu.2024.101573>.

Fortune's (1987, <doi:10.1007/BF01840357>) algorithm is a very efficient method to perform Voronoi tessellation and Delaunay triangulation. This package is a port of the original code published in the early 1990's by Steven Fortune.

The d3.js framework with the plugins d3-voronoi-map, d3-voronoi-treemap and d3-weighted-voronoi
        are used to generate Voronoi treemaps in R and in a shiny application.
        The computation of the Voronoi treemaps are based on Nocaj and Brandes (2012)
        <doi:10.1111/j.1467-8659.2012.03078.x>.