Automates the process of creating a scale bar and north arrow in
    any package that uses base graphics to plot in R. Bounding box tools help find
    and manipulate extents. Finally, there is a function to automate the process
    of setting margins, plotting the map, scale bar, and north arrow, and resetting
    graphic parameters upon completion.

Functions for conventionally formatting descriptive stats,
 reshaping data frames and formatting R output as HTML.

Pretty, human readable formatting of quantities.
    Time intervals: '1337000' -> '15d 11h 23m 20s'.
    Vague time intervals: '2674000' -> 'about a month ago'.
    Bytes: '1337' -> '1.34 kB'.
    Rounding: '99' with 3 significant digits -> '99.0'
    p-values: '0.00001' -> '<0.0001'.
    Colors: '#FF0000' -> 'red'.
    Quantities: '1239437' -> '1.24 M'.

The prevalence package provides Frequentist and Bayesian methods for prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available on the user's system. JAGS can be downloaded from <https://mcmc-jags.sourceforge.io/>.

Easy and efficient access to the API provided by 'Prevedere', 
  an industry insights and predictive analytics company. Query and 
  download indicators, models and workbenches built with 'Prevedere' for further 
  analysis and reporting <https://www.prevedere.com/>.

Implements the American Heart Association (AHA) Predicting
    Risk of cardiovascular disease EVENTs (PREVENT) equations from Khan
    SS, Matsushita K, Sang Y, and colleagues (2024)
    <doi:10.1161/CIRCULATIONAHA.123.067626>.

For working with the 'Prevision.io' AI model management platform's API <https://prevision.io/>.

Provides functions for both likelihood-based
    and Bayesian analysis of spatially referenced prevalence data. For a tutorial on the use of the R package, see Giorgi and Diggle (2017) <doi:10.18637/jss.v078.i08>.

Spatial estimation of a prevalence surface
    or a relative risks surface, using data from a Demographic and Health
    Survey (DHS) or an analog survey, see Larmarange et al. (2011)
    <doi:10.4000/cybergeo.24606>.