Man pages for bbuchsbaum/multivarious
Extensible Data Structures for Multivariate Analysis

add_nodeadd a pre-processing stage
add_node.prepperAdd a pre-processing node to a pipeline
apply_rotationApply rotation
apply_transformapply a pre-processing transform
biplot.pcaBiplot for PCA Objects (Enhanced with ggrepel)
bi_projectorConstruct a bi_projector instance
bi_projector_unionA Union of Concatenated 'bi_projector' Fits
block_indicesget block_indices
block_indices.multiblock_projectorExtract the Block Indices from a Multiblock Projector
block_lengthsget block_lengths
bootstrapBootstrap Resampling for Multivariate Models
bootstrap_pcaFast, Exact Bootstrap for PCA Results from 'pca' function
centercenter a data matrix
classifierConstruct a Classifier
classifier.discriminant_projectorCreate a k-NN classifier for a discriminant projector
classifier.multiblock_biprojectorMultiblock Bi-Projector Classifier
classifier.projectorcreate classifier from a projector
coef.composed_projectorGet Coefficients of a Composed Projector
coef.cross_projectorExtract coefficients from a cross_projector object
coef.multiblock_projectorCoefficients for a Multiblock Projector
colscalescale a data matrix
componentsget the components
compose_partial_projectorCompose Multiple Partial Projectors
compose_projectorCompose Two Projectors
concat_pre_processorsbind together blockwise pre-processors
cPCAplusContrastive PCA++ (cPCA++) Performs Contrastive PCA++...
cross_projectorTwo-way (cross) projection to latent components
cvCross-validation Framework
cv_genericGeneric cross-validation engine
discriminant_projectorConstruct a Discriminant Projector
feature_importanceEvaluate feature importance
feature_importance.classifierEvaluate Feature Importance for a Classifier
freshGet a fresh pre-processing node cleared of any cached data
geneigGeneralized Eigenvalue Decomposition
group_meansCompute column-wise mean in X for each factor level of Y
init_transforminitialize a transform
inverse_projectionInverse of the Component Matrix
inverse_projection.composed_projectorCompute the Inverse Projection for a Composed Projector
inverse_projection.cross_projectorDefault inverse_projection method for cross_projector
is_orthogonalis it orthogonal
is_orthogonal.projectorStricter check for true orthogonality
measure_interblock_transfer_errorCompute inter-block transfer error metrics for a...
measure_reconstruction_errorCompute reconstruction-based error metrics
multiblock_biprojectorCreate a Multiblock Bi-Projector
multiblock_projectorCreate a Multiblock Projector
nblocksget the number of blocks
ncompGet the number of components
nystrom_approxNyström approximation for kernel-based decomposition (Unified...
partial_inverse_projectionPartial Inverse Projection of a Columnwise Subset of...
partial_inverse_projection.cross_projectorPartial Inverse Projection of a Subset of the Loading Matrix...
partial_inverse_projection.regressPartial Inverse Projection for a 'regress' Object
partial_projectPartially project a new sample onto subspace
partial_project.composed_partial_projectorPartial Project Through a Composed Partial Projector
partial_project.cross_projectorPartially project data for a cross_projector
partial_projectorConstruct a partial projector
passa no-op pre-processing step
pcaPrincipal Components Analysis (PCA)
pca_outliersPCA Outlier Diagnostics
perm_ciPermutation Confidence Intervals
perm_testGeneric Permutation-Based Test
predict.classifierPredict Class Labels using a Classifier Object
predict.discriminant_projectorPredict method for a discriminant_projector, supporting LDA...
predict.rf_classifierPredict Class Labels using a Random Forest Classifier Object
prepprepare a dataset by applying a pre-processing pipeline
prinangCalculate Principal Angles Between Subspaces
principal_anglesPrincipal angles (two sub‑spaces)
print.bootstrap_pca_resultPrint method for bootstrap_pca_result
print.classifierPretty Print Method for 'classifier' Objects
print.concat_pre_processorPrint a concat_pre_processor object
print.multiblock_biprojectorPretty Print Method for 'multiblock_biprojector' Objects
print.pcaPrint Method for PCA Objects
print.perm_testPrint Method for perm_test Objects
print.perm_test_pcaPrint Method for perm_test_pca Objects
print.prepperPrint a prepper pipeline
print.pre_processorPrint a pre_processor object
print.regressPretty Print Method for 'regress' Objects
print.rf_classifierPretty Print Method for 'rf_classifier' Objects
projectNew sample projection
project_blockProject a single "block" of data onto the subspace
project_block.multiblock_projectorProject Data onto a Specific Block
project.cross_projectorproject a cross_projector instance
project.nystrom_approxProject new data using a Nyström approximation model
projectorConstruct a 'projector' instance
project_varsProject one or more variables onto a subspace
rank_scoreCalculate Rank Score for Predictions
reconstructReconstruct the data
reconstruct.composed_projectorReconstruct Data from Scores using a Composed Projector
reconstruct_newReconstruct new data in a model's subspace
reconstruct.pcaReconstruct Data from PCA Results
refitrefit a model
regressMulti-output linear regression
reprocessapply pre-processing parameters to a new data matrix
reprocess.cross_projectorreprocess a cross_projector instance
residualizeCompute a regression model for each column in a matrix and...
residualsObtain residuals of a component model fit
reverse_transformreverse a pre-processing transform
rf_classifierconstruct a random forest wrapper classifier
rf_classifier.projectorCreate a random forest classifier
robust_inv_vTvPossibly use ridge-regularized inversion of crossprod(v)
rotateRotate a Component Solution
rotate.pcaRotate PCA Loadings
scoresRetrieve the component scores
screeplotScreeplot for PCA
screeplot.pcaScreeplot for PCA
sdevstandard deviations
shapeShape of the Projector
shape.cross_projectorshape of a cross_projector instance
standardizecenter and scale each vector of a matrix
std_scoresCompute standardized component scores
std_scores.svdCalculate Standardized Scores for SVD results
subspace_similarityCompute subspace similarity
summary.composed_projectorSummarize a Composed Projector
svd_wrapperSingular Value Decomposition (SVD) Wrapper
topktop-k accuracy indicator
transferTransfer data from one domain/block to another via a latent...
transfer.cross_projectorTransfer from X domain to Y domain (or vice versa) in a...
transposeTranspose a model
truncatetruncate a component fit
truncate.composed_projectorTruncate a Composed Projector
variables_usedIdentify Original Variables Used by a Projector
vars_for_componentIdentify Original Variables for a Specific Component
bbuchsbaum/multivarious documentation built on July 16, 2025, 11:04 p.m.