Euclidean

Calculates two-dimensional Euclidean distance between all points and dimension means.

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

Euclidean function

<dl><dt>data</dt>
<dd>an <code>n x 2</code> matrix or data frame.</dd></dl>

Arguments

Euclidean Distance from Dimension Means — Euclidean

<dl>

<dt>data</dt>
<dd>an <code>n x 2</code> matrix or data frame.</dd>

</dl>

Euclidean: Euclidean Distance from Dimension Means

Description

Usage

Value

Arguments

Examples