Shiny wrappers for the RGL package. This package exposes RGL's
    ability to export WebGL visualization in a shiny-friendly format.

A 'shiny' interface for a simpler use of the 'sbm' R package. 
    It also contains useful functions to easily explore the 'sbm' package results. 
    With this package you should be able to use the stochastic block model 
    without any knowledge in R, get automatic reports and nice visuals, as 
    well as learning the basic functions of 'sbm'.

Capture screenshots in 'Shiny' applications. Screenshots can either be
    of the entire viewable page, or a specific section of the page. The captured
    image is automatically downloaded as a PNG image, or it can also be saved on
    the server. Powered by the 'html2canvas' JavaScript library.

Add a searchbar widget to your 'Shiny' application. The widget
  quickly integrates with any existing element containing text to highlight
  matches. Highlighting is done with the 'JavaScript' library 'mark.js'. The
  widget includes buttons to cycle through multiple instances of the match and
  automatically scroll to the matches in an overflow element (or window). The
  widget also displays the total number of matches and which match is currently
  being cycled through. The widget is structured as a 'Bootstrap 3' input
  group.

Provides a select control widget for 'Shiny'. It is easily
    customizable, and one can easily use HTML in the items and KaTeX to
    type mathematics.

Create in-app purchasing and subscriptions through 'Servicebot' payment using the 'Stripe' framework.

Provides function shinyShortcut() that, 
    when given the base directory of a shiny application, will produce an
    executable file that runs the shiny app directly in the user's
    default browser. Tested on both windows and unix machines. Inspired
    by and borrowing from 
    <http://www.mango-solutions.com/wp/2017/03/shiny-based-tablet-or-desktop-app/>.

Provides interactive plotting for mathematical models of infectious disease spread. Users can choose from a variety of common built-in ordinary differential equation (ODE) models (such as the SIR, SIRS, and SIS models), or create their own. This latter flexibility allows 'shinySIR' to be applied to simple ODEs from any discipline. The package is a useful teaching tool as students can visualize how changing different parameters can impact model dynamics, with minimal knowledge of coding in R. The built-in models are inspired by those featured in Keeling and Rohani (2008) <doi:10.2307/j.ctvcm4gk0> and Bjornstad (2018) <doi:10.1007/978-3-319-97487-3>.