Clustering via Nonparametric Density Estimation: The R Package pdfCluster

Adelchi Azzalini and Giovanna Menardi

Journal of Statistical Software, 2014, vol. 057, issue i11

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.

Date: 2014-05-06
References: View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v057i11/v57i11.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... Cluster_1.0-2.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v057i11/v57i11.R

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:057:i11

DOI: 10.18637/jss.v057.i11

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().