Bivariate Correlations Calculation and Visualization
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Documentation for package ‘linkspotter’ version 1.3.0
Help Pages
| BeEFdiscretization.numfact | BeEF: Best Equal-Frequency discretization |
| BeEFdiscretization.numnum | BeEF: Best Equal-Frequency discretization (for a couple of quantitative variables) |
| clusterVariables | Variable clustering (using Normal Mixture Modeling for Model-Based Clustering : mclust) |
| corCouplesToMatrix | Couples to matrix |
| createShinyAppFolder | Ready-for-deployment shiny app folder creation |
| EFdiscretization | EF: Equal-Frequency discretization |
| is.not.informative.variable | Is a vector an non informative variable |
| linkspotterComplete | Linkspotter complete runner |
| linkspotterGraph | Linkspotter graph runner |
| linkspotterGraphOnMatrix | Linkspotter graph on matrix |
| linkspotterOnFile | Process Linkspotter on an external file |
| linkspotterUI | Linkspotter user interface runner |
| matrixToCorCouples | Matrix to couples |
| maxNMI | Maximal Normalized Mutual Information (MaxNMI) |
| multiBivariateCorrelation | Calculation of all the bivariate correlations in a dataframe |
| NormalizedMI | Maximal Normalized Mutual Information (MaxNMI) function for 2 categorical variables |