Flexible Procedures for Clustering

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Documentation for package ‘fpc’ version 2.1-10

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A B C D E F H I J K L M N P R S T U W Z

fpc-package fpc package overview

-- A --

adcoord Asymmetric discriminant coordinates
ancoord Asymmetric neighborhood based discriminant coordinates
awcoord Asymmetric weighted discriminant coordinates

-- B --

batcoord Bhattacharyya discriminant projection
batvarcoord Bhattacharyya discriminant projection
bhattacharyya.dist Bhattacharyya distance between Gaussian distributions
bhattacharyya.matrix Matrix of pairwise Bhattacharyya distances

-- C --

calinhara Calinski-Harabasz index
can Generation of the tuning constant for regression fixed point clusters
cat2bin Recode nominal variables to binary variables
claraCBI Interface functions for clustering methods
classifdist Classification of unclustered points
classifnp Classification of unclustered points
clucols Sets of colours and symbols for cluster plotting
clugrey Sets of colours and symbols for cluster plotting
clujaccard Jaccard similarity between logical vectors
clusexpect Expected value of the number of times a fixed point cluster is found
cluster.stats Cluster validation statistics
cluster.varstats Variablewise statistics for clusters
clusterboot Clusterwise cluster stability assessment by resampling
clusym Sets of colours and symbols for cluster plotting
cmahal Generation of tuning constant for Mahalanobis fixed point clusters.
con.comp Connectivity components of an undirected graph
confusion Misclassification probabilities in mixtures
cov.wml Weighted Covariance Matrices (Maximum Likelihood)
cweight Weight function for AWC

-- D --

dbscan DBSCAN density reachability and connectivity clustering
dbscanCBI Interface functions for clustering methods
dipp.tantrum Simulates p-value for dip test
diptest.multi Diptest for discriminant coordinate projection
discrcoord Discriminant coordinates/canonical variates
discrete.recode Recodes mixed variables dataset
discrproj Linear dimension reduction for classification
distancefactor Factor for dissimilarity of mixed type data
distcritmulti Distance based validity criteria for large data sets
disthclustCBI Interface functions for clustering methods
disthclusttreeCBI Interface functions for clustering methods
distnoisemclustCBI Interface functions for clustering methods
disttrimkmeansCBI Interface functions for clustering methods
dridgeline Density along the ridgeline
dudahart2 Duda-Hart test for splitting

-- E --

extract.mixturepars Extract parameters for certain components from mclust

-- F --

fixmahal Mahalanobis Fixed Point Clusters
fixreg Linear Regression Fixed Point Clusters
flexmixedruns Fitting mixed Gaussian/multinomial mixtures with flexmix
fpclusters Extracting clusters from fixed point cluster objects
fpclusters.mfpc Mahalanobis Fixed Point Clusters
fpclusters.rfpc Linear Regression Fixed Point Clusters
fpmi Mahalanobis Fixed Point Clusters

-- H --

hclustCBI Interface functions for clustering methods
hclusttreeCBI Interface functions for clustering methods

-- I --

itnumber Number of regression fixed point cluster iterations

-- J --

jittervar Jitter variables in a data matrix

-- K --

kmeansCBI Interface functions for clustering methods
kmeansruns k-means with estimating k and initialisations

-- L --

lcmixed flexmix method for mixed Gaussian/multinomial mixtures
localshape Local shape matrix

-- M --

mahalanodisc Mahalanobis for AWC
mahalanofix Mahalanobis distances from center of indexed points
mahalanofuz Mahalanobis distances from center of indexed points
mahalCBI Interface functions for clustering methods
mahalconf Mahalanobis fixed point clusters initial configuration
mergenormals Clustering by merging Gaussian mixture components
mergenormCBI Interface functions for clustering methods
mergeparameters New parameters from merging two Gaussian mixture components
minsize Minimum size of regression fixed point cluster
mixdens Density of multivariate Gaussian mixture, mclust parameterisation
mixpredictive Prediction strength of merged Gaussian mixture
mvdcoord Mean/variance differences discriminant coordinates

-- N --

ncoord Neighborhood based discriminant coordinates
noisemclustCBI Interface functions for clustering methods
nselectboot Selection of the number of clusters via bootstrap

-- P --

pamk Partitioning around medoids with estimation of number of clusters
pamkCBI Interface functions for clustering methods
piridge Ridgeline Pi-function
piridge.zeroes Extrema of two-component Gaussian mixture
plot.clboot Clusterwise cluster stability assessment by resampling
plot.dbscan DBSCAN density reachability and connectivity clustering
plot.mfpc Mahalanobis Fixed Point Clusters
plot.rfpc Linear Regression Fixed Point Clusters
plotcluster Discriminant projection plot.
predict.dbscan DBSCAN density reachability and connectivity clustering
prediction.strength Prediction strength for estimating number of clusters
print.clboot Clusterwise cluster stability assessment by resampling
print.dbscan DBSCAN density reachability and connectivity clustering
print.mfpc Mahalanobis Fixed Point Clusters
print.predstr Prediction strength for estimating number of clusters
print.rfpc Linear Regression Fixed Point Clusters
print.summary.mergenorm Clustering by merging Gaussian mixture components
print.summary.mfpc Mahalanobis Fixed Point Clusters
print.summary.rfpc Linear Regression Fixed Point Clusters
print.varwisetables Variablewise statistics for clusters

-- R --

randcmatrix Random partition matrix
randconf Generate a sample indicator vector
regem Mixture Model ML for Clusterwise Linear Regression
regmix Mixture Model ML for Clusterwise Linear Regression
rFace "Face-shaped" clustered benchmark datasets
rfpi Linear Regression Fixed Point Clusters
ridgeline Ridgeline computation
ridgeline.diagnosis Ridgeline plots, ratios and unimodality

-- S --

simmatrix Extracting intersections between clusters from fpc-object
solvecov Inversion of (possibly singular) symmetric matrices
speccCBI Interface functions for clustering methods
sseg Position in a similarity vector
summary.mergenorm Clustering by merging Gaussian mixture components
summary.mfpc Mahalanobis Fixed Point Clusters
summary.rfpc Linear Regression Fixed Point Clusters

-- T --

tdecomp Root of singularity-corrected eigenvalue decomposition
tonedata Tone perception data
trimkmeansCBI Interface functions for clustering methods

-- U --

unimodal.ind Is a fitted denisity unimodal or not?

-- W --

weightplots Ordered posterior plots
wfu Weight function (for Mahalabobis distances)

-- Z --

zmisclassification.matrix Matrix of misclassification probabilities between mixture components