Package: multiblock 0.8.10

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.

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

multiblock_0.8.10.tar.gz
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multiblock.pdf |multiblock.html✨
multiblock/json (API)
NEWS

# Install 'multiblock' in R:
install.packages('multiblock', repos = c('https://khliland.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/khliland/multiblock/issues

Pkgdown/docs site:https://khliland.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • candies - Sensory assessment of candies.
  • mobile - ECSI Mobile Mobile Phone Provider Dataset
  • potato - Sensory, rheological, chemical and spectroscopic analysis of potatoes.
  • simulated - Data simulated to have certain characteristics.
  • wine - Wines of Val de Loire

On CRAN:

Conda:

cpp

6.05 score 18 stars 21 scripts 381 downloads 61 exports 93 dependencies

Last updated from:433a4e652b. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK215
linux-devel-x86_64OK239
source / vignettesOK353
linux-release-arm64OK216
linux-release-x86_64OK232
macos-release-arm64OK151
macos-release-x86_64OK326
macos-oldrel-arm64OK170
macos-oldrel-x86_64OK240
windows-develOK199
windows-releaseOK263
windows-oldrelOK378
wasm-releaseOK160

Exports:ascablock.data.frameblock.preprocessblockexplccaclassifycoefplotcompnamescorrplotcvanovacvsegmentsdiscodummycodeexplvarextended.model.framegcagpagsvdhogsvdhpcaifajiveloading.weightsloadingplotloadingsloadingweightplotlplslplsCVlplsDatamaagemaageSeqmbplsmbrdamcoamcolorsmfaMSEPmvrValstatspcapcagcapcppcrpermutationplotplsrpoplspredplotR2RMSEProsarosa.classifyscascoreplotscoressmbplssoplssopls_pmsopls_pm_multiplestatistimeplotunique_combosvalidationplot

Dependencies:abindade4backportsbdsmatrixbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11crayonDerivdoBydplyrfarverforecastFormulafracdiffgenalggenericsggplot2gluegtableHDANOVAhmsisobandlabelinglatticeleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamixlmmodelrmultcompmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpixmappkgconfigplotrixplsplsVarSelpracmapraznikprettyunitsprogresspurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRSpectraS7sandwichscalesspSparseMSSBtoolsstringistringrsurvivalTH.datatibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

A. Data handling

Rendered fromvignette_A_data.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2021-04-30
Started: 2021-04-07

B. Basic analysis

Rendered fromvignette_B_basic.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2021-04-07
Started: 2021-04-07

C. Unsupervised multiblock analysis

Rendered fromvignette_C_unsupervised.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2021-09-07
Started: 2021-04-07

D. ASCA

Rendered fromvignette_D_asca.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2021-04-07
Started: 2021-04-07

E. Supervised multiblock analysis

Rendered fromvignette_E_supervised.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2022-10-29
Started: 2021-04-07

F. Complex multiblock analysis

Rendered fromvignette_F_complex.Rmdusingknitr::rmarkdownon Apr 17 2026.

Last update: 2021-09-07
Started: 2021-04-07

Readme and manuals

Help Manual

Help pageTopics
Single- and Two-Block Methodsbasic
Block-wise indexable data.frameblock.data.frame
Sensory assessment of candies.candies
Canonical Correlation Analysis - CCAcca
Methods With Complex Linkagecomplex
Vector of component namescompnames
Distinctive and Common Components with SCA - DISCOdisco
DISCO-SCA rotation.DISCOsca
Dummy-coding of a single vectordummycode
Explained predictor varianceexplvar
Extracting the Extended Model Frame from a Formula or Fitextended.model.frame
Generalized Canonical Analysis - GCAgca
Generalized Procrustes Analysis - GPAgpa
Generalised Singular Value Decomposition - GSVDgsvd
Higher Order Generalized SVD - HOGSVDhogsvd
Hierarchical Principal component analysis - HPCAhpca
Inter-battery Factor Analysis - IFAifa
Joint and Individual Variation Explained - JIVEjive
L-PLS regressionlpls
Result functions for L-PLS objects ('lpls')lplsCV lpls_results plot.lpls predict.lpls
L-PLS data simulation for exo-type analysislplsData
Måge plotmaage maageSeq
Multiblock Partial Least Squares - MB-PLSmbpls
Multiblock Redundancy Analysis - mbRDAmbrda
Multiple Co-Inertia Analysis - MCOAmcoa
Colour palette generation from matrix of RGB valuesmcolors
Multiple Factor Analysis - MFAmfa
ECSI Mobile Mobile Phone Provider Datasetmobile
Plot Functions for Multiblock Objectsbiplot.multiblock corrplot corrplot.default corrplot.multiblock corrplot.mvr loadingplot.multiblock loadingweightplot multiblock_plots scoreplot.multiblock
Result Functions for Multiblock Objectsloadings.multiblock multiblock_results print.multiblock scores.multiblock summary.multiblock
MSEP, RMSEP and R2 of the MB-PLS modelMSEP.mbpls mvrVal mvrValstats.mbpls R2.mbpls RMSEP.mbpls
Principal Component Analysis - PCApca
PCA-GCApcagca
Parallel and Orthogonalised Partial Least Squares - PO-PLSpopls
Sensory, rheological, chemical and spectroscopic analysis of potatoes.potato
Predict Method for MBPLSpredict.mbpls
Preprocessing of block datablock.preprocess preprocess
Response Oriented Sequential Alternation - ROSArosa
Plotting functions for ROSA modelsbarplot.rosa image.rosa rosa_plots
Result functions for ROSA modelsblockexpl coef.rosa loadings.rosa predict.rosa print.rosa print.rosaexpl rosa.classify rosa_results scores.rosa summary.rosa
Simultaneous Component Analysis - SCAsca
Data simulated to have certain characteristics.simulated
Sparse Multiblock Partial Least Squares - sMB-PLSsmbpls
Total, direct, indirect and additional effects in SO-PLS-PM.print.SO_TDI print.SO_TDI_multiple sopls_pm sopls_pm_multiple SO_TDI
Sequential and Orthogonalized PLS (SO-PLS)sopls
Scores, loadings and plots for sopls objectsbiplot.sopls corrplot.sopls loadingplot.sopls loadings.sopls scoreplot.sopls scores.sopls sopls_plots
Result functions for SO-PLS modelsclassify classify.sopls coef.sopls cvanova cvanova.default cvanova.sopls pcp pcp.default pcp.sopls plot.cvanova predict.sopls print.cvanova print.sopls R2.sopls residuals.sopls RMSEP.sopls sopls_results summary.cvanova summary.sopls
Structuration des Tableaux à Trois Indices de la Statistique - STATISstatis
Supervised Multiblock Methodssupervised
Unique combinations of blocksunique_combos
Unsupervised Multiblock Methodsunsupervised
Wines of Val de Loirewine