linkspotter: Bivariate Correlations Calculation and Visualization

Compute and visualize using the 'visNetwork' package all the bivariate correlations of a dataframe. Several and different types of correlation coefficients (Pearson's r, Spearman's rho, Kendall's tau, distance correlation, maximal information coefficient and equal-freq discretization-based maximal normalized mutual information) are used according to the variable couple type (quantitative vs categorical, quantitative vs quantitative, categorical vs categorical).

Version: 1.3.0
Depends: R (≥ 3.2.0)
Imports: shiny, visNetwork, infotheo, minerva, energy, mclust, rAmCharts, pbapply, ggplot2, dplyr, tidyr, shinybusy
Suggests: knitr, rmarkdown
Published: 2020-07-23
Author: Alassane Samba [aut, cre], Orange [cph]
Maintainer: Alassane Samba <alassane.samba at orange.com>
BugReports: https://github.com/sambaala/linkspotter/issues
License: MIT + file LICENSE
URL: https://github.com/sambaala/linkspotter
NeedsCompilation: no
Materials: README NEWS
CRAN checks: linkspotter results

Documentation:

Reference manual: linkspotter.pdf
Vignettes: Introduction to Linkspotter

Downloads:

Package source: linkspotter_1.3.0.tar.gz
Windows binaries: r-devel: linkspotter_1.3.0.zip, r-release: linkspotter_1.3.0.zip, r-oldrel: linkspotter_1.3.0.zip
macOS binaries: r-release (arm64): linkspotter_1.3.0.tgz, r-release (x86_64): linkspotter_1.3.0.tgz, r-oldrel: linkspotter_1.3.0.tgz
Old sources: linkspotter archive

Linking:

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