pair_scagnostics

Calculates scagnostic values for every numeric variable pair in a dataset.

We provide a tidy data structure and visualisations for multiple or grouped  variable correlations,
general association measures scagnostics and other pairwise scores  suitable for numerical, ordinal and nominal variables.
Supported measures include distance correlation, maximal information, ace correlation, Kendall's tau, and polychoric correlation.

Catherine Hurley

bullseye

Visualising Multiple Pairwise Variable Correlations and Other
Scores

Amit Chinwan

pair_scagnostics function

<dl><dt>d</dt>
<dd>A dataframe</dd>
<dt>scagnostic</dt>
<dd>a character vector for the scagnostic to be calculated. Subset of "Outlying",
"Stringy", "Striated", "Clumpy", "Sparse", "Skewed", "Convex", "Skinny" or "Monotonic"</dd>
<dt>handle.na</dt>
<dd>If TRUE uses pairwise complete observations.</dd>
<dt>...</dt>
<dd>other arguments</dd></dl>

Arguments

Graph-theoretic scagnostics values — pair_scagnostics

<dl>

<dt>d</dt>
<dd>A dataframe</dd>


<dt>scagnostic</dt>
<dd>a character vector for the scagnostic to be calculated. Subset of "Outlying",
"Stringy", "Striated", "Clumpy", "Sparse", "Skewed", "Convex", "Skinny" or "Monotonic"</dd>


<dt>handle.na</dt>
<dd>If TRUE uses pairwise complete observations.</dd>


<dt>...</dt>
<dd>other arguments</dd>

</dl>

pair_scagnostics: Graph-theoretic scagnostics values

Description

Usage

Value

Arguments

Details

References

Examples