Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume
             of polytopes given by (i) a set of points, (ii) linear inequalities or (iii) Minkowski sum of segments
             (a.k.a. zonotopes). There are three algorithms for volume estimation as well as algorithms
             for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for
             estimating copulas useful in computational finance. Methods implemented in 'volesti' are described
             in A. Chalkis and V. Fisikopoulos (2022) <doi:10.32614/RJ-2021-077> and references therein.

Craft polished tables and plots in Markdown reports. 
             Simply choose whether to treat your data as counts or metrics, 
             and the package will automatically generate well-designed default tables and plots for you.
             Boiled down to the basics, with labeling features and simple interactive reports.
             All functions are 'tidyverse' compatible.

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>.