Compute Scagnostics on Pairs of Numeric Variables in a Data Set
Compute scagnostics on all possible scatter plots for the given data
Compute selected scagnostics on subsets
Drawing the alphahull
Drawing the Convex Hull
Drawing the MST
Compute robust clumpy scagnostic measure using MST
Compute clumpy scagnostic measure using MST
Compute adjusted clumpy measure using MST
Compute convex scagnostic measure
Distance correlation index.
Measure of Spearman Correlation
Compute outlying scagnostic measure using MST
Compute skewed scagnostic measure using MST
Compute skinny scagnostic measure
Compute sparse scagnostic measure using MST
Compute adjusted sparse measure using the alpha hull
Spline based index.
Compute striated scagnostic measure using MST
Compute angle adjusted striated measure using MST
Compute stringy scagnostic measure using MST
Measure of Discreteness
Pre-processing to generate scagnostic measures
Calculate the top scagnostic for each pair of variables
Calculate the top pair of variables or group for each scagnostic
Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.