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.


Reference manual

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0.8.0 by Kristian Hovde Liland, a month ago,

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Browse source code at

Authors: Kristian Hovde Liland [aut, cre] , Solve Sæbø [ctb] , Stefan Schrunner [rev]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports ade4, car, FactoMineR, geigen, knitr, lme4, MASS, MFAg, mixlm, plotrix, pls, plsVarSel, pracma, progress, r.jive, Rcpp, RegularizedSCA, RGCCA, RSpectra, SSBtools

Suggests rmarkdown

Linking to Rcpp, RcppEigen

See at CRAN