mdendro: Variable-Group Methods for Agglomerative Hierarchical Clustering

A collection of methods for agglomerative hierarchical clustering strategies on a matrix of distances, implemented using the variable-group approach introduced in Fernandez and Gomez (2008) <doi:10.1007/s00357-008-9004-x>. Descriptive measures to analyze the resulting hierarchical trees are also provided. In addition to the usual clustering methods, two parameterized methods are provided to explore an infinite family of hierarchical clustering strategies. When there are ties in proximity values, the hierarchical trees obtained are unique and independent of the order of the elements in the input matrix.

Version: 1.0.1
Depends: R (≥ 3.5.0)
Imports: rJava (≥ 0.9.8)
Published: 2018-12-06
Author: Alberto Fernandez ORCID iD [aut, cre], Sergio Gomez ORCID iD [aut]
Maintainer: Alberto Fernandez <alberto.fernandez at urv.cat>
License: LGPL-2.1
NeedsCompilation: no
SystemRequirements: Java (>= 6)
CRAN checks: mdendro results

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Reference manual: mdendro.pdf
Package source: mdendro_1.0.1.tar.gz
Windows binaries: r-devel: mdendro_1.0.1.zip, r-release: mdendro_1.0.1.zip, r-oldrel: not available
OS X binaries: r-release: mdendro_1.0.1.tgz, r-oldrel: not available
Old sources: mdendro archive

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