Linkspotter is a package of R software that allows to **calculate** and **visualize** using a graph all the **bivariate links** of a dataset.

Its main features are:

- calculation of several correlation matrices corresponding to different link coefficients.
- clustering of variables using an unsupervised learning.
- supervised discretization of one or a couple of variables.

It also offers a customizable user interface, allowing to:

- Visualize the links using a graph (the variables correspond to the nodes and the links correspond to the edges)
- View the distribution of each variable using its histogram or barplot
- Visualize a link between a couple of variables using scatter plots, box plots, etc.

Available link coefficients are:

- Pearson’s r
- Spearman’s rho
- Kendall’s tau
- the Maximal Information Coefficient (MIC)
- the distance correlation
- the Maximal Normalized Mutual Information (MaxNMI)

The MaxNMI is a bivariate link coefficient, which uses a supervised discretization called Best Equal-Frequency Discretization (BeEF). Both are introduced by Linkspotter. The interest of this new link coefficient is that it enables to assess and compare the link between a couple of variables, whatever their types (quantitative vs qualitative, quantitative vs quantitative, qualitative vs qualitative).

Linkspotter uses and combines some features coming from other R packages, namely infotheo, minerva, energy, mclust, Hmisc, shiny, visNetwork and rAmCharts.

Please refer to the Github repository for any contribution.

** License**: MIT + file LICENSE