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>.

Price comparisons within or between countries provide an overall measure of the relative difference in prices, often denoted as price levels. This package provides index number methods for such price comparisons (e.g., The World Bank, 2011, <doi:10.1596/978-0-8213-9728-2>). Moreover, it contains functions for sampling and characterizing price data.