Package: pdfCluster 1.0-4

Menardi Giovanna

pdfCluster: Cluster Analysis via Nonparametric Density Estimation

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.

Authors:Menardi Giovanna [aut, cre], Azzalini Adelchi [aut], Rosolin Tiziana [ctb]

pdfCluster_1.0-4.tar.gz
pdfCluster_1.0-4.tar.gz(r-4.5-noble)pdfCluster_1.0-4.tar.gz(r-4.4-noble)
pdfCluster_1.0-4.tgz(r-4.4-emscripten)pdfCluster_1.0-4.tgz(r-4.3-emscripten)
pdfCluster.pdf |pdfCluster.html
pdfCluster/json (API)
NEWS

# Install 'pdfCluster' in R:
install.packages('pdfCluster', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.71 score 5 stars 11 packages 191 scripts 2.7k downloads 6 mentions 17 exports 7 dependencies

Last updated 2 years agofrom:84703331f9. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linux-x86_64OKNov 28 2024

Exports:adj.rand.indexdbsgroupsh.normhprop2fkepdfpdfClassificationpdfClusterplotplot.dbsplot.kepdfplot.pdfClustershowsummarysummary.dbssummary.kepdfsummary.pdfCluster

Dependencies:abindgeometrylinproglpSolvemagicRcppRcppProgress

Readme and manuals

Help Manual

Help pageTopics
The pdfCluster package: summary informationpdfCluster-package
Adjusted Rand indexadj.rand.index
Density-based silhouette information methodsdbs dbs,matrix,numeric-method dbs,matrix-method dbs,pdfCluster,missing-method dbs,pdfCluster-method dbs-methods
Class "dbs"dbs-class show,dbs-method summary.dbs
Extracts groupsgroups
Normal optimal choice of smoothing parameter in density estimationh.norm
Sample smoothing parameters in adaptive density estimationhprop2f
Kernel estimate of a probability density function.kepdf
Class "kepdf"kepdf-class show,kepdf-method summary.kepdf
Olive oil dataoliveoil
Classification of low density datapdfClassification
Clustering via nonparametric density estimationpdfCluster pdfCluster,data.frame-method pdfCluster,matrix-method pdfCluster,numeric-method pdfCluster,pdfCluster-method pdfCluster-methods
Class "pdfCluster"pdfCluster-class show,pdfCluster-method summary.pdfCluster
Methods for function plotplot-methods
Plot objects of class dbsplot,dbs,missing-method plot,dbs-method plot.dbs
Plot objects of class kepdfplot,kepdf,missing-method plot,kepdf-method plot.kepdf
Plot objects of class pdfClusterplot,pdfCluster,missing-method plot,pdfCluster-method plot.pdfCluster
Methods for Function showshow-methods
Methods for Function summarysummary,dbs-method summary,kepdf-method summary,pdfCluster-method summary-methods
Wine datawine