Calculates sums of squares for uni- or multi-dimensional numeric data using the
distance matrix.

Implements cluster-polarization coefficient for measuring distributional
polarization in single or multiple dimensions, as well as associated functions.
Contains support for hierarchical clustering, k-means, partitioning around medoids,
density-based spatial clustering with noise, and manually imposed cluster membership.
Mehlhaff (2024) <doi:10.1017/S0003055423001041>.

Isaac Mehlhaff

Implementation of Cluster-Polarization Coefficient

SS function

<dl><dt>data</dt>
<dd>a numeric vector or <code>n x k</code> matrix or data frame.</dd>
<dt>...</dt>
<dd>arguments passed to <code><a href="/link/dist?package=CPC&version=2.6.2" data-mini-rdoc="CPC::dist">dist</a>()</code>.</dd></dl>

Arguments

Sum-of-Squares Calculation — SS

<dl>

<dt>data</dt>
<dd>a numeric vector or <code>n x k</code> matrix or data frame.</dd>


<dt>...</dt>
<dd>arguments passed to <code><a href='https://rdrr.io/r/stats/dist.html'>dist</a>()</code>.</dd>

</dl>

SS: Sum-of-Squares Calculation

Description

Usage

Value

Arguments

Examples