fpc v2.1-11.1

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Flexible Procedures for Clustering

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.

Functions in fpc

Name Description
cat2bin Recode nominal variables to binary variables
cluster.stats Cluster validation statistics
calinhara Calinski-Harabasz index
cluster.varstats Variablewise statistics for clusters
cmahal Generation of tuning constant for Mahalanobis fixed point clusters.
clusterboot Clusterwise cluster stability assessment by resampling
cweight Weight function for AWC
can Generation of the tuning constant for regression fixed point clusters
dbscan DBSCAN density reachability and connectivity clustering
fixreg Linear Regression Fixed Point Clusters
flexmixedruns Fitting mixed Gaussian/multinomial mixtures with flexmix
adcoord Asymmetric discriminant coordinates
dudahart2 Duda-Hart test for splitting
ancoord Asymmetric neighborhood based discriminant coordinates
awcoord Asymmetric weighted discriminant coordinates
batcoord Bhattacharyya discriminant projection
discrcoord Discriminant coordinates/canonical variates
classifdist Classification of unclustered points
extract.mixturepars Extract parameters for certain components from mclust
kmeansCBI Interface functions for clustering methods
confusion Misclassification probabilities in mixtures
con.comp Connectivity components of an undirected graph
dipp.tantrum Simulates p-value for dip test
discrete.recode Recodes mixed variables dataset
clucols Sets of colours and symbols for cluster plotting
kmeansruns k-means with estimating k and initialisations
discrproj Linear dimension reduction for classification
distcritmulti Distance based validity criteria for large data sets
distancefactor Factor for dissimilarity of mixed type data
dridgeline Density along the ridgeline
diptest.multi Diptest for discriminant coordinate projection
fpc-package fpc package overview
neginc Neg-entropy normality index for cluster validation
fpclusters Extracting clusters from fixed point cluster objects
nselectboot Selection of the number of clusters via bootstrap
mahalconf Mahalanobis fixed point clusters initial configuration
itnumber Number of regression fixed point cluster iterations
jittervar Jitter variables in a data matrix
lcmixed flexmix method for mixed Gaussian/multinomial mixtures
mvdcoord Mean/variance differences discriminant coordinates
piridge.zeroes Extrema of two-component Gaussian mixture
localshape Local shape matrix
ncoord Neighborhood based discriminant coordinates
plotcluster Discriminant projection plot.
wfu Weight function (for Mahalabobis distances)
randcmatrix Random partition matrix
mixdens Density of multivariate Gaussian mixture, mclust parameterisation
mergenormals Clustering by merging Gaussian mixture components
xtable Partition crosstable with empty clusters
randconf Generate a sample indicator vector
pamk Partitioning around medoids with estimation of number of clusters
zmisclassification.matrix Matrix of misclassification probabilities between mixture components
piridge Ridgeline Pi-function
bhattacharyya.dist Bhattacharyya distance between Gaussian distributions
bhattacharyya.matrix Matrix of pairwise Bhattacharyya distances
clujaccard Jaccard similarity between logical vectors
mixpredictive Prediction strength of merged Gaussian mixture
clusexpect Expected value of the number of times a fixed point cluster is found
cvnn Cluster validation based on nearest neighbours
cov.wml Weighted Covariance Matrices (Maximum Likelihood)
findrep Finding representatives for cluster border
fixmahal Mahalanobis Fixed Point Clusters
prediction.strength Prediction strength for estimating number of clusters
ridgeline.diagnosis Ridgeline plots, ratios and unimodality
simmatrix Extracting intersections between clusters from fpc-object
solvecov Inversion of (possibly singular) symmetric matrices
sseg Position in a similarity vector
rFace "Face-shaped" clustered benchmark datasets
unimodal.ind Is a fitted denisity unimodal or not?
mahalanofix Mahalanobis distances from center of indexed points
mahalanodisc Mahalanobis for AWC
weightplots Ordered posterior plots
mergeparameters New parameters from merging two Gaussian mixture components
minsize Minimum size of regression fixed point cluster
regmix Mixture Model ML for Clusterwise Linear Regression
tdecomp Root of singularity-corrected eigenvalue decomposition
ridgeline Ridgeline computation
tonedata Tone perception data
cdbw CDbw-index for cluster validation
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Date 2018-01-05
License GPL
URL http://www.homepages.ucl.ac.uk/~ucakche/
NeedsCompilation no
Packaged 2018-07-20 09:19:29 UTC; hornik
Repository CRAN
Date/Publication 2018-07-20 12:43:31 UTC
X-CRAN-Original-Maintainer Christian Hennig
X-CRAN-Comment Orphaned and corrected on 2018-07-20 as check problems were not corrected despite reminders.

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