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Multiblock object

A common object type for many multiblock methods.

Basic methods

Single- and two-block methods

basic
Single- and Two-Block Methods
pca()
Principal Component Analysis - PCA
reexports pcr plsr MSEP R2 RMSEP coefplot cvsegments loading.weights loadingplot loadings mvrValstats predplot scoreplot scores validationplot
Objects exported from other packages
cca()
Canonical Correlation Analysis - CCA
ifa()
Inter-battery Factor Analysis - IFA
gsvd()
Generalised Singular Value Decomposition - GSVD

Unsupervised methods

unsupervised
Unsupervised Multiblock Methods
sca()
Simultaneous Component Analysis - SCA
gca()
Generalized Canonical Analysis - GCA
gpa()
Generalized Procrustes Analysis - GPA
mfa()
Multiple Factor Analysis - MFA
pcagca()
PCA-GCA
disco()
Distinctive and Common Components with SCA - DISCO
DISCOsca()
DISCO-SCA rotation.
hpca()
Hierarchical Principal component analysis - HPCA
mcoa()
Multiple Co-Inertia Analysis - MCOA
jive()
Joint and Individual Variation Explained - JIVE
statis()
Structuration des Tableaux à Trois Indices de la Statistique - STATIS
hogsvd()
Higher Order Generalized SVD - HOGSVD

Supervised methods

supervised
Supervised Multiblock Methods
mbpls()
Multiblock Partial Least Squares - MB-PLS
smbpls()
Sparse Multiblock Partial Least Squares - sMB-PLS
sopls()
Sequential and Orthogonalized PLS (SO-PLS)
predict(<sopls>) coef(<sopls>) print(<sopls>) summary(<sopls>) classify() R2(<sopls>) RMSEP(<sopls>) pcp() cvanova() print(<cvanova>) summary(<cvanova>) plot(<cvanova>) residuals(<sopls>)
Result functions for SO-PLS models
loadings(<sopls>) scores(<sopls>) scoreplot(<sopls>) loadingplot(<sopls>) corrplot(<sopls>) biplot(<sopls>)
Scores, loadings and plots for sopls objects
maage() maageSeq()
Måge plot
popls()
Parallel and Orthogonalised Partial Least Squares - PO-PLS
rosa()
Response Oriented Sequential Alternation - ROSA
predict(<rosa>) coef(<rosa>) print(<rosa>) summary(<rosa>) blockexpl() print(<rosaexpl>) rosa.classify() scores(<rosa>) loadings(<rosa>)
Result functions for ROSA models
image(<rosa>) barplot(<rosa>)
Plotting functions for ROSA models
mbrda()
Multiblock Redundancy Analysis - mbRDA
R2(<mbpls>) MSEP(<mbpls>) RMSEP(<mbpls>)
MSEP, RMSEP and R2 of the MB-PLS model
predict(<mbpls>)
Predict Method for MBPLS

Complex methods

complex
Methods With Complex Linkage
lpls()
L-PLS regression
plot(<lpls>) predict(<lpls>) lplsCV()
Result functions for L-PLS objects (lpls)
lplsData()
L-PLS data simulation for exo-type analysis
sopls_pm() print(<SO_TDI>) sopls_pm_multiple() print(<SO_TDI_multiple>)
Total, direct, indirect and additional effects in SO-PLS-PM.

ASCA

asca()
Analysis of Variance Simultaneous Component Analysis - ASCA
print(<asca>) summary(<asca>) print(<summary.asca>) loadings(<asca>) scores(<asca>) projections()
ASCA Result Methods
loadingplot(<asca>) scoreplot(<asca>)
ASCA Result Methods

Utility functions

block.data.frame()
Block-wise indexable data.frame
compnames()
Vector of component names
dummycode()
Dummy-coding of a single vector
explvar()
Explained predictor variance
mcolors()
Colour palette generation from matrix of RGB values
reexports pcr plsr MSEP R2 RMSEP coefplot cvsegments loading.weights loadingplot loadings mvrValstats predplot scoreplot scores validationplot
Objects exported from other packages
unique_combos()
Unique combinations of blocks
extended.model.frame()
Extracting the Extended Model Frame from a Formula or Fit
block.preprocess()
Preprocessing of block data

Datasets

candies
Sensory assessment of candies.
potato
Sensory, rheological, chemical and spectroscopic analysis of potatoes.
simulated
Data simulated to have certain characteristics.
wine
Wines of Val de Loire