birth

Birth and death rates for 70 countries.

datasets

The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance
measures and centroid computation. Further cluster methods
include hard competitive learning, neural gas, and QT
clustering. There are numerous visualization methods for
cluster results (neighborhood graphs, convex cluster hulls,
barcharts of centroids, ...), and bootstrap methods for the
analysis of cluster stability.

Friedrich Leisch

flexclust

Flexible Cluster Algorithms

Evgenia Dimitriadou

birth function

A data frame with 70 observations on the following 2 variables.<dl class="dl-horizontal">
 <dt>birth:</dt><dd>birth rate (in percent)</dd>
 <dt>death:</dt><dd>death rate (in percent)</dd>
 </dl>

Format

Birth and Death Rates — birth

A data frame with 70 observations on the following 2 variables.<dl class='dl-horizontal'>
 <dt>birth:</dt><dd>birth rate (in percent)</dd>
 <dt>death:</dt><dd>death rate (in percent)</dd>
 </dl>

birth: Birth and Death Rates

Description

Usage

Arguments

Format

References