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fpc (version 1.1-1)

Fixed point clusters, clusterwise regression and discriminant plots

Description

Fuzzy and crisp fixed point cluster analysis based on Mahalanobis distance and linear regression fixed point clusters. Semi-explorative, semi-model-based clustering methods, operating on n*p data, do not need prespecification of number of clusters, produce overlapping clusters. Symmetric and asymmetric discriminant projections separate groups optimally, used to visualize the separation of groupings. Corresponding plot methods. Clusterwise linear regression by normal mixture modeling. Cluster validation statistics for distance based clustering.

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Install

install.packages('fpc')

Monthly Downloads

16,363

Version

1.1-1

License

GPL

Last Published

April 22nd, 2004

Functions in fpc (1.1-1)