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_0.8.10.tgz(r-4.6-x86_64)multiblock_0.8.10.tgz(r-4.6-arm64)multiblock_0.8.10.tgz(r-4.5-x86_64)multiblock_0.8.10.tgz(r-4.5-arm64)
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multiblock_0.8.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
multiblock/json (API)

# 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

6.21 score 18 stars 30 scripts 409 downloads 61 exports 93 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-arm64OK197
linux-devel-x86_64OK230
source / vignettesOK275
linux-release-arm64OK206
linux-release-x86_64OK228
macos-release-arm64OK156
macos-release-x86_64OK280
macos-oldrel-arm64OK141
macos-oldrel-x86_64OK351
windows-develOK168
windows-releaseOK183
windows-oldrelOK196
wasm-releaseOK172

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

Dependencies:abindade4backportsbdsmatrixbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11crayonDerivdoBydplyrfarverforecastFormulafracdiffgenalggenericsggplot2gluegtableHDANOVAhmsisobandlabelinglatticeleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamixlmmodelrmultcompmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpixmappkgconfigplotrixplsplsVarSelpracmapraznikprettyunitsprogresspurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRSpectraS7sandwichscalesspSparseMSSBtoolsstringistringrsurvivalTH.datatibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

E. Supervised multiblock analysis
Supervised methods | Formatting data for multiblock analyses | Multiblock Partial Least Squares - MB-PLS | Modelling | Summaries and plotting | Sparse Multiblock Partial Least Squares - sMB-PLS | Plotting | Sequential and orthogonalised PLS - SO-PLS | Måge plot | Loadings | Scores | Prediction | Validation | Principal Components of Predictions | CVANOVA | Parallel and Orthgonalised Partial Least Squares - PO-PLS | Scores and loadings | Response Oriented Sequential Alternation - ROSA | Image plots | Multiblock Redundancy Analysis - mbRDA | Loadings and scores

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

C. Unsupervised multiblock analysis
Unsupervised methods | Formatting data for multiblock data analysis | Method interfaces | Shared sample mode | Shared variable mode | Common output elements across methods | Scores and loadings | Plot from imported package

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

F. Complex multiblock analysis
Complex data structures | L-PLS | Simulated L-shaped data | Exo-L-PLS | Endo-L-PLS | L-PLS cross-validation | SO-PLS Path Modelling | Single SO-PLS-PM model | Multiple paths in an SO-PLS-PM model

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

A. Data handling
Read from file | Data pre-processing | Re-coding categorical data | Data structures for multiblock analysis | Create list of blocks | Create data.frame of blocks

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

B. Basic analysis
Basic methods | Prepare data | Modelling | Common output elements across methods | Scores and loadings

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

D. ASCA
ANOVA Simultaneous Component Analysis -- ASCA | Simulated data | Formula interface | ASCA modelling | Scores | Loadings

Last update: 2021-04-07
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