blockcluster: Co-Clustering Package for Binary, Categorical, Contingency and Continuous Data-Sets

Simultaneous clustering of rows and columns, usually designated by biclustering, co-clustering or block clustering, is an important technique in two way data analysis. It consists of estimating a mixture model which takes into account the block clustering problem on both the individual and variables sets. The 'blockcluster' package provides a bridge between the C++ core library build on top of the 'STK++' library, and the R statistical computing environment. This package allows to co-cluster binary <doi:10.1016/j.csda.2007.09.007>, contingency <doi:10.1080/03610920903140197>, continuous <doi:10.1007/s11634-013-0161-3> and categorical data-sets <doi:10.1007/s11222-014-9472-2>. It also provides utility functions to visualize the results. This package may be useful for various applications in fields of Data mining, Information retrieval, Biology, computer vision and many more. More information about the project and comprehensive tutorial can be found on the link mentioned in URL.

Version: 4.5.5
Depends: R (≥ 4.1.0), rtkore (≥ 1.6.10)
Imports: methods
LinkingTo: Rcpp, rtkore (≥ 1.6.10)
Published: 2024-02-23
DOI: 10.32614/CRAN.package.blockcluster
Author: Serge Iovleff [aut, cre], Parmeet Singh Bhatia [aut], Josselin Demont [ctb], Vincent Brault [ctb], Vincent Kubicki [ctb], Gerard Goavert [ctb], Christophe Biernacki [ctb], Gilles Celeux [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff at>
License: GPL (≥ 3)
Copyright: Inria
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: blockcluster citation info
Materials: NEWS
CRAN checks: blockcluster results


Reference manual: blockcluster.pdf
Vignettes: blockcluster tutorial


Package source: blockcluster_4.5.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): blockcluster_4.5.5.tgz, r-oldrel (arm64): blockcluster_4.5.5.tgz, r-release (x86_64): blockcluster_4.5.5.tgz, r-oldrel (x86_64): blockcluster_4.5.5.tgz
Old sources: blockcluster archive

Reverse dependencies:

Reverse suggests: diceR


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