Useful libraries for building a Java based GUI under R are provided.

The CommonMark specification <https://github.github.com/gfm/> defines
    a rationalized version of markdown syntax. This package uses the 'cmark' 
    reference implementation for converting markdown text into various formats
    including html, latex and groff man. In addition it exposes the markdown
    parse tree in xml format. Also includes opt-in support for GFM extensions
    including tables, autolinks, and strikethrough text.

Estimate bivariate common mean vector under copula models with known correlation. In the current version, available copulas are the Clayton, Gumbel, Frank, Farlie-Gumbel-Morgenstern (FGM), and normal copulas. See Shih et al. (2019) <doi:10.1080/02331888.2019.1581782> and Shih et al. (2021) <under review> for details under the FGM and general copulas, respectively.

'Java' JAR files for the Apache Commons Mathematics Library for use by users and other packages.

Computing comorbidity indices and scores such as the weighted Charlson
  score (Charlson, 1987 <doi:10.1016/0021-9681(87)90171-8>) and the Elixhauser
  comorbidity score (Elixhauser, 1998 <doi:10.1097/00005650-199801000-00004>)
  using ICD-9-CM or ICD-10 codes (Quan, 2005 <doi:10.1097/01.mlr.0000182534.19832.83>).
  Australian and Swedish modifications of the Charlson Comorbidity Index are available
  as well (Sundararajan, 2004 <doi:10.1016/j.jclinepi.2004.03.012> and Ludvigsson, 2021 
  <doi:10.2147/CLEP.S282475>), together with different weighting algorithms for both
  the Charlson and Elixhauser comorbidity scores.

Using polygenic scores (PGS, or PRS/GRS for binary outcomes), 
    this package allows to investigate shared predisposition between different 
    conditions, and do fast association analysis, export plots and views
    of the PGS distribution using 'ggplot2' object.

Provides static and interactive maps of the Comoro Islands at four
    administrative levels: country, island, prefecture, and commune. Includes
    tools for choropleth visualisation using 'ggplot2' and 'leaflet', and
    functions to retrieve the underlying spatial datasets as 'sf' objects.