Title: Correcting the Coverage of Credible Sets from Bayesian Genetic
Suggests: covr, dplyr, knitr, mvtnorm, rmarkdown, testthat, pkgdown
Imports: magrittr, stats, matrixStats, Rcpp

Title: Correcting AUC for Measurement Error
Author: Bernard Rosner, Shelley Tworoger, Weiliang Qiu
Description: Correcting area under ROC (AUC) for measurement error based on probit-shift model.

Title: Functions and Methods for Correspondence Regression
Description: A collection of tools for correspondence regression, i.e. the
correspondence analysis of the crosstabulation of a categorical variable Y
in function of another one X, where X can in turn be made up of the
combination of various categorical variables. Consequently, correspondence
regression can be used to analyze the effects for a polytomous or
Depends: R (>= 3.1.0), graphics, rgl, stats
Suggests: datasets, grDevices, MASS, polytomous

Depends: R (>= 3.1.0), graphics, diagram, rgl, stats
Suggests: datasets, grDevices, MASS, knitr

Depends: R (>= 3.2.0), graphics, diagram, rgl, stats
Imports: data.table, ellipse, gplots, utils

Title: Multivariate Data Generation by Permutation
Author: Pascal van Kooten <kootenpv@gmail.com>,
Maintainer: Pascal van Kooten <kootenpv@gmail.com>
Description: Through permutations, obtain a multivariate distribution between univariate variables by specifying a correlation matrix.

Description: Lightweight package for computing different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, biweight correlations, distance correlations and more. Relies on the easystats ecosystem (Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>).
Imports: stats, boot, insight (>= 0.8.0), bayestestR (>= 0.5.0),
parameters (>= 0.5.0), effectsize (>= 0.2.0)
Suggests: BayesFactor, dplyr, energy, ggcorrplot, ggplot2, Hmisc,
knitr, lme4, polycor, ppcor, psych, rmcorr, testthat, tidyr,
Mattan S. Ben-Shachar [ctb] (<https://orcid.org/0000-0002-4287-4801>),

Imports: stats, insight (>= 0.8.0), bayestestR (>= 0.5.0), parameters