# fpc v2.2-7

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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 | |

ancoord | Asymmetric neighborhood based discriminant coordinates | |

calinhara | Calinski-Harabasz index | |

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

bhattacharyya.dist | Bhattacharyya distance between Gaussian distributions | |

bhattacharyya.matrix | Matrix of pairwise Bhattacharyya distances | |

adcoord | Asymmetric discriminant coordinates | |

awcoord | Asymmetric weighted discriminant coordinates | |

batcoord | Bhattacharyya discriminant projection | |

cdbw | CDbw-index for cluster validation | |

cat2bin | Recode nominal variables to binary variables | |

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

cluster.varstats | Variablewise statistics for clusters | |

classifdist | Classification of unclustered points | |

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

cluster.stats | Cluster validation statistics | |

clusterbenchstats | Run and validate many clusterings | |

clustatsum | Compute and format cluster validation statistics | |

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

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

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

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

clusterboot | Clusterwise cluster stability assessment by resampling | |

diptest.multi | Diptest for discriminant coordinate projection | |

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

dbscan | DBSCAN density reachability and connectivity clustering | |

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

cweight | Weight function for AWC | |

cvnn | Cluster validation based on nearest neighbours | |

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

distancefactor | Factor for dissimilarity of mixed type data | |

discrete.recode | Recodes mixed variables dataset | |

confusion | Misclassification probabilities in mixtures | |

discrproj | Linear dimension reduction for classification | |

discrcoord | Discriminant coordinates/canonical variates | |

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

findrep | Finding representatives for cluster border | |

fixmahal | Mahalanobis Fixed Point Clusters | |

fpc-package | fpc package overview | |

clujaccard | Jaccard similarity between logical vectors | |

fpclusters | Extracting clusters from fixed point cluster objects | |

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

dridgeline | Density along the ridgeline | |

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

localshape | Local shape matrix | |

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

mahalconf | Mahalanobis fixed point clusters initial configuration | |

fixreg | Linear Regression Fixed Point Clusters | |

dudahart2 | Duda-Hart test for splitting | |

mergenormals | Clustering by merging Gaussian mixture components | |

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

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

mahalanofix | Mahalanobis distances from center of indexed points | |

itnumber | Number of regression fixed point cluster iterations | |

mahalanodisc | Mahalanobis for AWC | |

kmeansCBI | Interface functions for clustering methods | |

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

plotcluster | Discriminant projection plot. | |

mvdcoord | Mean/variance differences discriminant coordinates | |

ridgeline | Ridgeline computation | |

jittervar | Jitter variables in a data matrix | |

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

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

ncoord | Neighborhood based discriminant coordinates | |

valstat.object | Cluster validation statistics - object | |

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

regmix | Mixture Model ML for Clusterwise Linear Regression | |

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

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

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

mixpredictive | Prediction strength of merged Gaussian mixture | |

xtable | Partition crosstable with empty clusters | |

randconf | Generate a sample indicator vector | |

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

piridge | Ridgeline Pi-function | |

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

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

minsize | Minimum size of regression fixed point cluster | |

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

tdecomp | Root of singularity-corrected eigenvalue decomposition | |

sseg | Position in a similarity vector | |

stupidkcentroids | Stupid k-centroids random clustering | |

stupidkaven | Stupid average dissimilarity random clustering | |

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

randcmatrix | Random partition matrix | |

weightplots | Ordered posterior plots | |

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

stupidknn | Stupid nearest neighbour random clustering | |

tonedata | Tone perception data | |

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

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

stupidkfn | Stupid farthest neighbour random clustering | |

wfu | Weight function (for Mahalabobis distances) | |

No Results! |

## Last month downloads

## Details

Date | 2020-06-25 |

License | GPL |

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

NeedsCompilation | no |

Packaged | 2020-06-25 10:36:21 UTC; chrish |

Repository | CRAN |

Date/Publication | 2020-06-26 06:10:17 UTC |

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