Title: Bayesian Network Modeling and Analysis
Description: A Shiny web application for creating interactive Bayesian Network models,
learning the structure and parameters of Bayesian networks, and utilities for classical
Authors@R: person("Paul", "Govan", email = "pgovan1@aggienetwork.com", role = c("aut", "cre"))
Imports: bnlearn, d3heatmap, lattice, networkD3, rhandsontable, shiny,
Packaged: 2016-07-20 23:37:57 UTC; paulgovan

Description: A 'Shiny' web application for creating interactive Bayesian Network models,
Packaged: 2016-10-25 20:20:17 UTC; paulgovan

learning the structure and parameters of Bayesian networks, and utilities for classic
Imports: bnlearn, heatmaply, lattice, networkD3, plotly, rintrojs,
Packaged: 2017-07-12 01:38:27 UTC; paulgovan

Authors@R: person("Paul", "Govan", email = "pgovan1@aggienetwork.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1821-8492"))
shiny, shinyAce, shinydashboard, shinytest, shinyWidgets,
Packaged: 2018-12-02 02:09:14 UTC; paulgovan
Author: Paul Govan [aut, cre] (<https://orcid.org/0000-0002-1821-8492>)

Title: Sample Size and Power for Comparing Inequality Constrained
Description: A collection of methods to determine the required sample size for
the evaluation of inequality constrained hypotheses by means of a Bayes
factor. Alternatively, for a given sample size, the unconditional error
probabilities or the expected conditional error probabilities can be
determined. Additional material on the methods in this package is
available in Klaassen, F., Hoijtink, H. & Gu, X. (2019)

Title: Plot Positive and Negative Predictive Values for Medical Tests
Authors@R: c(person("Gorka", "Navarrete", email = "gorkang@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7678-8656")))
Description: Functions to plot and help understand positive and negative predictive values (PPV and NPV), and their relationship with sensitivity, specificity, and prevalence. See Akobeng, A.K. (2007) <doi:10.1111/j.1651-2227.2006.00180.x> for a theoretical overview of the technical concepts and Navarrete et al. (2015) for a practical explanation about the importance of their understanding <doi:10.3389/fpsyg.2015.01327>.
Imports: dplyr, reshape2, ggplot2, tidyr, magrittr, tibble, ggforce,
Suggests: testthat, knitr, rmarkdown, covr
Author: Gorka Navarrete [aut, cre] (<https://orcid.org/0000-0001-7678-8656>)