A set of pricing and expository functions that should
    be useful in teaching a course on financial derivatives.

Convert 'gtsummary' tables and plain data frames into clinical-style
    Rich Text Format, plain text, Word, PDF, and HTML outputs using 'reporter',
    with managed widths, pagination, indentation, spanning headers, and optional
    intermediate data exports.

Discrete event simulation (DES) involves modeling of systems
   having discrete, i.e. abrupt, state changes. For instance, when a job
   arrives to a queue, the queue length abruptly increases by 1.  This
   package is an R implementation of the event-oriented approach to DES;
   see the tutorial in Matloff (2008) 
   <http://heather.cs.ucdavis.edu/~matloff/156/PLN/DESimIntro.pdf>.

Provides a comprehensive framework for early epidemic detection through school absenteeism surveillance. The package offers three core functionalities: (1) simulation of population structures, epidemic spread, and resulting school absenteeism patterns; (2) implementation of surveillance models that generate alerts for impending epidemics based on absenteeism data and (3) evaluation of alert timeliness and accuracy through alert time quality metrics to optimize model parameters. These tools enable public health officials and researchers to develop and assess early warning systems before implementation. Methods are based on research published in Vanderkruk et al. (2023) <doi:10.1186/s12889-023-15747-z> and Ward et al. (2019) <doi:10.1186/s12889-019-7521-7>.

Tools to read, write, create, and manipulate DESCRIPTION
    files.  It is intended for packages that create or manipulate other
    packages.

Designed for genomic and proteomic data analysis, enabling unbiased PubMed searching, protein interaction network visualization, and comprehensive data summarization. This package aims to help users identify novel targets within their data sets based on protein network interactions and publication precedence of target's association with research context based on literature precedence. Methods in this package are described in detail in: Douglas et al. (2025) <doi:10.1039/D5MO00160A>. Key functionalities of this package also leverage methodologies from previous works, such as:
  - Szklarczyk et al. (2023) <doi:10.1093/nar/gkac1000>
  - Winter (2017) <doi:10.32614/RJ-2017-066>.