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pdfCluster (version 1.0-4)

Cluster Analysis via Nonparametric Density Estimation

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.

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Version

Install

install.packages('pdfCluster')

Monthly Downloads

2,551

Version

1.0-4

License

GPL-2

Maintainer

Giovanna Menardi

Last Published

December 2nd, 2022

Functions in pdfCluster (1.0-4)

pdfCluster

Clustering via nonparametric density estimation
pdfClassification

Classification of low density data
plot,kepdf-method

Plot objects of class kepdf
summary-methods

Methods for Function summary
plot,dbs-method

Plot objects of class dbs
plot-methods

Methods for function plot
wine

Wine data
plot,pdfCluster-method

Plot objects of class pdfCluster
pdfCluster-class

Class "pdfCluster"
kepdf

Kernel estimate of a probability density function.
show-methods

Methods for Function show
pdfCluster-package

The pdfCluster package: summary information
oliveoil

Olive oil data
kepdf-class

Class "kepdf"
dbs

Density-based silhouette information methods
groups

Extracts groups
adj.rand.index

Adjusted Rand index
dbs-class

Class "dbs"
h.norm

Normal optimal choice of smoothing parameter in density estimation
hprop2f

Sample smoothing parameters in adaptive density estimation