birth

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

birth function

<url>http://www.uni-koeln.de/themen/statistik</url>

birth: Birth and Death Rates

Description

Usage

Arguments

source

References