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covalchemy: Constructing Joint Distributions with Control Over Statistical Properties

Synthesizing joint distributions from marginal densities, focusing on controlling key statistical properties such as correlation for continuous data, mutual information for categorical data, and inducing Simpson's Paradox. Generate datasets with specified correlation structures for continuous variables, adjust mutual information between categorical variables, and manipulate subgroup correlations to intentionally create Simpson's Paradox. Joe (1997) <doi:10.1201/b13150> Sklar (1959) <https://en.wikipedia.org/wiki/Sklar%27s_theorem>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: dplyr, ggplot2, mvtnorm, interp, clue, ggExtra, gridExtra, DescTools, MASS
Published: 2024-11-21
DOI: 10.32614/CRAN.package.covalchemy
Author: Naman Agrawal [aut, cre]
Maintainer: Naman Agrawal <naman.agr03 at gmail.com>
BugReports: https://github.com/namanlab/covalchemy/issues
License: GPL-3
URL: https://github.com/namanlab/covalchemy
NeedsCompilation: no
Materials: README
CRAN checks: covalchemy results

Documentation:

Reference manual: covalchemy.pdf

Downloads:

Package source: covalchemy_1.0.0.tar.gz
Windows binaries: r-devel: covalchemy_1.0.0.zip, r-release: covalchemy_1.0.0.zip, r-oldrel: covalchemy_1.0.0.zip
macOS binaries: r-release (arm64): covalchemy_1.0.0.tgz, r-oldrel (arm64): covalchemy_1.0.0.tgz, r-release (x86_64): covalchemy_1.0.0.tgz, r-oldrel (x86_64): covalchemy_1.0.0.tgz

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.