Author: Brecht Devleesschauwer [aut, cre],
Description: 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/>.
Imports: methods, utils, stats, graphics, grDevices, coda, rjags

Description: 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
Suggests: testthat (>= 2.1.0), knitr, covr
Author: Wil Davis [aut, cre] (<https://orcid.org/0000-0001-9780-2576>),

Description: For working with the 'Prevision.io' AI model management platform's API <https://prevision.io/>.
Imports: data.table, futile.logger, httr, jsonlite, Metrics, graphics,

Title: Prevalence to Incidence Calculations for Point-Prevalence
Authors@R: person("Niklas", "Willrich", email = "WillrichN@rki.de", role = c("aut", "cre"))
Description: 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.
Suggests: knitr, rmarkdown, testthat, ggplot2, purrr, gridExtra, tidyr
Packaged: 2019-03-07 13:15:20 UTC; WillrichN

Suggests: knitr, rmarkdown, testthat, ggplot2, gridExtra, tidyr
Packaged: 2019-06-18 11:05:37 UTC; WillrichN

Title: Data Pre-Processing for Bacterial Genome-Wide Association
Description: Standardize the pre-processing of genomic variants before
performing a bacterial genome-wide association study (bGWAS). prewas creates
a variant matrix (where each row is a variant, each column is a sample, and
the entries are presence - 1 - or absence - 0 - of the variant) that can be
used as input for bGWAS tools. When creating the binary variant matrix,
prewas can perform 3 pre-processing steps including: dealing with
multiallelic SNPs, (optional) dealing with SNPs in overlapping genes, and
choosing a reference allele. prewas can output matrices for use with both
SNP-based bGWAS and gene-based bGWAS. This method is described in Saund et
Suggests: testthat (>= 2.2.1), knitr (>= 1.24), rmarkdown (>= 1.15)
Author: Katie Saund [aut, cre] (<https://orcid.org/0000-0002-6214-6713>),