# fpc v2.2-9

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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.
Standardisation of cluster validation statistics by random clusterings and
comparison between many clustering methods and numbers of clusters based on
this.
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 | |

cdbw | CDbw-index for cluster validation | |

adcoord | Asymmetric discriminant coordinates | |

cat2bin | Recode nominal variables to binary variables | |

bhattacharyya.matrix | Matrix of pairwise Bhattacharyya distances | |

awcoord | Asymmetric weighted discriminant coordinates | |

batcoord | Bhattacharyya discriminant projection | |

bhattacharyya.dist | Bhattacharyya distance between Gaussian distributions | |

calinhara | Calinski-Harabasz index | |

can | Generation of the tuning constant for regression fixed point clusters | |

ancoord | Asymmetric neighborhood based discriminant coordinates | |

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

cluster.magazine | Run many clustering methods on many numbers of clusters | |

cluster.stats | Cluster validation statistics | |

clucols | Sets of colours and symbols for cluster plotting | |

clujaccard | Jaccard similarity between logical vectors | |

clustatsum | Compute and format cluster validation statistics | |

classifdist | Classification of unclustered points | |

cgrestandard | Standardise cluster validation statistics by random clustering results | |

cvnn | Cluster validation based on nearest neighbours | |

cweight | Weight function for AWC | |

cluster.varstats | Variablewise statistics for clusters | |

confusion | Misclassification probabilities in mixtures | |

con.comp | Connectivity components of an undirected graph | |

clusterbenchstats | Run and validate many clusterings | |

cov.wml | Weighted Covariance Matrices (Maximum Likelihood) | |

cqcluster.stats | Cluster validation statistics (version for use with clusterbenchstats | |

clusterboot | Clusterwise cluster stability assessment by resampling | |

dbscan | DBSCAN density reachability and connectivity clustering | |

dipp.tantrum | Simulates p-value for dip test | |

dudahart2 | Duda-Hart test for splitting | |

cmahal | Generation of tuning constant for Mahalanobis fixed point clusters. | |

discrete.recode | Recodes mixed variables dataset | |

diptest.multi | Diptest for discriminant coordinate projection | |

distrsimilarity | Similarity of within-cluster distributions to normal and uniform | |

findrep | Finding representatives for cluster border | |

dridgeline | Density along the ridgeline | |

fpc-package | fpc package overview | |

discrcoord | Discriminant coordinates/canonical variates | |

fixmahal | Mahalanobis Fixed Point Clusters | |

flexmixedruns | Fitting mixed Gaussian/multinomial mixtures with flexmix | |

mahalanodisc | Mahalanobis for AWC | |

distancefactor | Factor for dissimilarity of mixed type data | |

distcritmulti | Distance based validity criteria for large data sets | |

fixreg | Linear Regression Fixed Point Clusters | |

mahalanofix | Mahalanobis distances from center of indexed points | |

extract.mixturepars | Extract parameters for certain components from mclust | |

itnumber | Number of regression fixed point cluster iterations | |

kmeansCBI | Interface functions for clustering methods | |

discrproj | Linear dimension reduction for classification | |

jittervar | Jitter variables in a data matrix | |

mergenormals | Clustering by merging Gaussian mixture components | |

plotcluster | Discriminant projection plot. | |

mahalconf | Mahalanobis fixed point clusters initial configuration | |

pamk | Partitioning around medoids with estimation of number of clusters | |

fpclusters | Extracting clusters from fixed point cluster objects | |

piridge | Ridgeline Pi-function | |

mvdcoord | Mean/variance differences discriminant coordinates | |

ncoord | Neighborhood based discriminant coordinates | |

simmatrix | Extracting intersections between clusters from fpc-object | |

regmix | Mixture Model ML for Clusterwise Linear Regression | |

ridgeline | Ridgeline computation | |

prediction.strength | Prediction strength for estimating number of clusters | |

minsize | Minimum size of regression fixed point cluster | |

ridgeline.diagnosis | Ridgeline plots, ratios and unimodality | |

plot.valstat | Simulation-standardised plot and print of cluster validation statistics | |

mergeparameters | New parameters from merging two Gaussian mixture components | |

piridge.zeroes | Extrema of two-component Gaussian mixture | |

randconf | Generate a sample indicator vector | |

rFace | "Face-shaped" clustered benchmark datasets | |

weightplots | Ordered posterior plots | |

randomclustersim | Simulation of validity indexes based on random clusterings | |

mixpredictive | Prediction strength of merged Gaussian mixture | |

mixdens | Density of multivariate Gaussian mixture, mclust parameterisation | |

xtable | Partition crosstable with empty clusters | |

randcmatrix | Random partition matrix | |

stupidkaven | Stupid average dissimilarity random clustering | |

localshape | Local shape matrix | |

wfu | Weight function (for Mahalabobis distances) | |

neginc | Neg-entropy normality index for cluster validation | |

kmeansruns | k-means with estimating k and initialisations | |

lcmixed | flexmix method for mixed Gaussian/multinomial mixtures | |

tdecomp | Root of singularity-corrected eigenvalue decomposition | |

tonedata | Tone perception data | |

nselectboot | Selection of the number of clusters via bootstrap | |

zmisclassification.matrix | Matrix of misclassification probabilities between mixture components | |

solvecov | Inversion of (possibly singular) symmetric matrices | |

stupidkcentroids | Stupid k-centroids random clustering | |

sseg | Position in a similarity vector | |

unimodal.ind | Is a fitted denisity unimodal or not? | |

valstat.object | Cluster validation statistics - object | |

stupidkfn | Stupid farthest neighbour random clustering | |

stupidknn | Stupid nearest neighbour random clustering | |

No Results! |

## Last month downloads

## Details

Date | 2020-12-06 |

License | GPL |

URL | https://www.unibo.it/sitoweb/christian.hennig/en/ |

NeedsCompilation | no |

Packaged | 2020-12-06 19:13:55 UTC; chrish |

Repository | CRAN |

Date/Publication | 2020-12-06 20:10:02 UTC |

imports | class , cluster , diptest , flexmix , graphics , grDevices , kernlab , MASS , mclust , methods , parallel , prabclus , robustbase , stats , utils |

suggests | mvtnorm , pdfCluster , tclust |

depends | R (>= 2.0) |

Contributors | Christian Hennig |

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