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 Predicting
    Risk of cardiovascular disease EVENTs (PREVENT) equations from Khan
    SS, Matsushita K, Sang Y, and colleagues (2023)
    <doi:10.1161/CIRCULATIONAHA.123.067626>, with optional comparison 
    with their de facto predecessor, the Pooled Cohort Equations from the 
	  American Heart Association and American College of Cardiology (2013)
	  <doi:10.1161/01.cir.0000437741.48606.98> and the revision to the Pooled 
	  Cohort Equations from Yadlowsky and colleagues (2018) 
	  <doi:10.7326/M17-3011>.

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

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>.

Functions to simulate point prevalence studies (PPSs) of healthcare-associated infections (HAIs) and to convert prevalence to incidence in steady state setups. 
    Companion package to the preprint Willrich et al., From prevalence to incidence - a new approach in the hospital setting;
    <doi:10.1101/554725> , where methods are explained in detail.

Estimate False Discovery Rates (FDRs) for importance metrics from
    random forest runs.

Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) 
    <doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.