multiblock: Multiblock Data Fusion in Statistics and Machine Learning

Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1) "Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences". This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting functions, several real data sets and six vignettes covering a range different applications.

Depends: R (≥ 3.5.0)
Imports: ade4, car, lme4, MASS, mixlm, plotrix, pls, plsVarSel, pracma, progress, Rcpp, RSpectra, SSBtools
LinkingTo: Rcpp, RcppEigen
Suggests: EMSC, FactoMineR, geigen, RGCCA (≥ 3.0.0), r.jive, rmarkdown, knitr
Published: 2024-03-11
DOI: 10.32614/CRAN.package.multiblock
Author: Kristian Hovde Liland ORCID iD [aut, cre], Solve Sæbø [ctb], Stefan Schrunner [rev]
Maintainer: Kristian Hovde Liland <kristian.liland at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: multiblock results


Reference manual: multiblock.pdf
Vignettes: A. Data handling
B. Basic analysis
C. Unsupervised multiblock analysis
E. Supervised multiblock analysis
F. Complex multiblock analysis


Package source: multiblock_0.8.8.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): multiblock_0.8.8.1.tgz, r-oldrel (arm64): multiblock_0.8.8.1.tgz, r-release (x86_64): multiblock_0.8.8.1.tgz, r-oldrel (x86_64): multiblock_0.8.8.1.tgz
Old sources: multiblock archive


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