Package index
-
multiblock-package
multiblock
- multiblock
-
scores(<multiblock>)
loadings(<multiblock>)
print(<multiblock>)
summary(<multiblock>)
- Result Functions for Multiblock Objects
-
scoreplot(<multiblock>)
loadingplot(<multiblock>)
loadingweightplot()
biplot(<multiblock>)
corrplot()
- Plot Functions for Multiblock Objects
-
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
- 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
- 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 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()
- 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
-
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