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fpc (version 2.1-5)

Flexible procedures for clustering

Description

Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.

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Version

Install

install.packages('fpc')

Monthly Downloads

21,008

Version

2.1-5

License

GPL

Maintainer

Christian Hennig

Last Published

January 21st, 2013

Functions in fpc (2.1-5)

Linear Regression Fixed Point Clusters

Local shape matrix

Tone perception data

Cluster validation statistics

Density along the ridgeline

Ordered posterior plots

discrete.recode

Recodes mixed variables dataset

Clustering by merging Gaussian mixture components

Mixture Model ML for Clusterwise Linear Regression

Distance based validity criteria for large data sets

Simulates p-value for dip test

Recode nominal variables to binary variables

Asymmetric neighborhood based discriminant coordinates

Factor for dissimilarity of mixed type data

Position in a similarity vector

DBSCAN density reachability and connectivity clustering

ridgeline.diagnosis

Ridgeline plots, ratios and unimodality

Clusterwise cluster stability assessment by resampling

Mahalanobis Fixed Point Clusters

"Face-shaped" clustered benchmark datasets

Ridgeline computation

Asymmetric discriminant coordinates

Extrema of two-component Gaussian mixture

fpc package overview

Partitioning around medoids with estimation of number of clusters

Mahalanobis fixed point clusters initial configuration

Linear dimension reduction for classification

prediction.strength

Prediction strength for estimating number of clusters

mergeparameters

New parameters from merging two Gaussian mixture components

Jitter variables in a data matrix

Random partition matrix

Root of singularity-corrected eigenvalue decomposition

Weight function (for Mahalabobis distances)

Calinski-Harabasz index

Diptest for discriminant coordinate projection

Misclassification probabilities in mixtures

Density of multivariate Gaussian mixture, mclust parameterisation

Generate a sample indicator vector

Asymmetric weighted discriminant coordinates

Classification of unclustered points

Duda-Hart test for splitting

Is a fitted denisity unimodal or not?

Expected value of the number of times a fixed point cluster is found

cluster.varstats

Variablewise statistics for clusters

Extracting clusters from fixed point cluster objects

Sets of colours and symbols for cluster plotting

Generation of the tuning constant for regression fixed point clusters

Generation of tuning constant for Mahalanobis fixed point clusters.

Discriminant coordinates/canonical variates

Minimum size of regression fixed point cluster

Bhattacharyya discriminant projection

Connectivity components of an undirected graph

Interface functions for clustering methods

Mean/variance differences discriminant coordinates

Number of regression fixed point cluster iterations

Mahalanobis for AWC

k-means with estimating k and initialisations

flexmix method for mixed Gaussian/multinomial mixtures

Discriminant projection plot.

Prediction strength of merged Gaussian mixture

Selection of the number of clusters via bootstrap

zmisclassification.matrix

Matrix of misclassification probabilities between mixture components

bhattacharyya.dist

Bhattacharyya distance between Gaussian distributions

Ridgeline Pi-function

Weight function for AWC

Extracting intersections between clusters from fpc-object

extract.mixturepars

Extract parameters for certain components from mclust

Weighted Covariance Matrices (Maximum Likelihood)

bhattacharyya.matrix

Matrix of pairwise Bhattacharyya distances

Neighborhood based discriminant coordinates

Inversion of (possibly singular) symmetric matrices

Jaccard similarity between logical vectors

Fitting mixed Gaussian/multinomial mixtures with flexmix

Mahalanobis distances from center of indexed points