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.


multiblock

Lifecycle: experimental CRAN Status

Installation

# Install release version from CRAN  
install.packages("multiblock")  
# Install development version from GitHub  
devtools::install_github("khliland/multiblock")

Multiblock book

This package contains a large variety of the methods described in Age K. Smilde, Tormod Næs and Kristian Hovde Liland's book:

Multiblock Data Fusion in Statistics and Machine Learning
- Applications in the Natural and Life Sciences

Published by Wiley in May 2022.

Contents

  • Functions and vignettes organised into:
    • data handling
    • basic methods
    • unsupervised methods
    • ASCA
    • supervised methods
    • methods for complex structures
  • A selection of datasets
  • Common framework and plotting routines

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("multiblock")

0.8.11 by Kristian Hovde Liland, 3 months ago


https://khliland.github.io/multiblock/, https://github.com/khliland/multiblock/


Report a bug at https://github.com/khliland/multiblock/issues/


Browse source code at https://github.com/cran/multiblock


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


Documentation:   PDF Manual  


GPL (>= 2) license


Imports ade4, car, HDANOVA, MASS, mixlm, plotrix, pls, plsVarSel, pracma, progress, Rcpp, RSpectra, SSBtools

Suggests EMSC, FactoMineR, geigen, RGCCA, r.jive, rmarkdown, knitr

Linking to Rcpp, RcppEigen


See at CRAN