Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Clustering via Nonparametric Density Estimation: The R Package pdfCluster | Azzalini | Journal of Statistical Software
Authors: Adelchi Azzalini, Giovanna Menardi
Title: Clustering via Nonparametric Density Estimation: The R Package pdfCluster
Abstract: The R package pdfCluster performs cluster analysis based on a nonparametric estimate of the density of the observed variables. Functions are provided to encompass the whole process of clustering, from kernel density estimation, to clustering itself and subsequent graphical diagnostics. After summarizing the main aspects of the methodology, we describe the features and the usage of the package, and finally illustrate its application with the aid of two data sets.

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Paper: Clustering via Nonparametric Density Estimation: The R Package pdfCluster     Download PDF (Downloads: 4374)
Supplements:
pdfCluster_1.0-2.tar.gz: R source package Download (Downloads: 224; 52KB)
v57i11.R: R example code from the paper Download (Downloads: 258; 1KB)
DOI: 10.18637/jss.v057.i11

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.