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pdfCluster  

Cluster Analysis via Nonparametric Density Estimation
View on CRAN: Click here


Download and install pdfCluster package within the R console
Install from CRAN:
install.packages("pdfCluster")

Install from Github:
library("remotes")
install_github("cran/pdfCluster")

Install by package version:
library("remotes")
install_version("pdfCluster", "1.0-4")



Attach the package and use:
library("pdfCluster")
Maintained by
Menardi Giovanna
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-03-01
Latest Update: 2022-12-02
Description:
Cluster analysis via nonparametric density estimation is performed. Operationally, the kernel method is used throughout to estimate the density. Diagnostics methods for evaluating the quality of the clustering are available. The package includes also a routine to estimate the probability density function obtained by the kernel method, given a set of data with arbitrary dimensions.
How to cite:
Menardi Giovanna (2011). pdfCluster: Cluster Analysis via Nonparametric Density Estimation. R package version 1.0-4, https://cran.r-project.org/web/packages/pdfCluster. Accessed 23 May. 2025.
Previous versions and publish date:
0.1-8 (2011-03-01 08:32), 0.1-9 (2011-04-01 23:07), 0.1-10 (2011-06-15 20:04), 0.1-13 (2011-08-22 21:47), 1.0-0 (2012-06-05 13:08), 1.0-1 (2013-11-18 10:50), 1.0-2 (2014-04-30 13:06), 1.0-3 (2018-12-04 12:10)
Other packages that cited pdfCluster R package
View pdfCluster citation profile
Other R packages that pdfCluster depends, imports, suggests or enhances
Complete documentation for pdfCluster
Functions, R codes and Examples using the pdfCluster R package
Some associated functions: adj.rand.index . dbs-class . dbs . groups . h.norm . hprop2f . kepdf-class . kepdf . oliveoil . pdfClassification . pdfCluster-class . pdfCluster-package . pdfCluster . plot-methods . plot.dbs . plot.kepdf . plot.pdfCluster . show-methods . summary-methods . wine . 
Some associated R codes: pdfCluster.R . zzz.R .  Full pdfCluster package functions and examples
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