add_node                add a pre-processing stage
apply_rotation          Apply rotation
apply_transform         apply a pre-processing transform
bi_projector            Construct a bi_projector instance
bi_projector_union      A Union of Concatenated 'bi_projector' Fits
block_indices           get block_indices
block_lengths           get block_lengths
bootstrap               Bootstrap Resampling for Multivariate Models
bootstrap.pca           PCA Bootstrap Resampling
center                  center a data matrix
classifier              Construct a Classifier
classifier.discriminant_projector
                        Create a k-NN classifier for a discriminant
                        projector
classifier.multiblock_biprojector
                        Multiblock Bi-Projector Classifier
classifier.projector    create 'classifier' from a 'projector'
coef.cross_projector    Extract coefficients from a cross_projector
                        object
colscale                scale a data matrix
components              get the components
compose_projector       Compose Two Projectors
compose_projectors      Projector Composition
concat_pre_processors   bind together blockwise pre-processors
convert_domain          Transfer data from one input domain to another
                        via common latent space
cross_projector         Two-way (cross) projection to latent components
discriminant_projector
                        Construct a Discriminant Projector
fresh                   Get a fresh pre-processing node cleared of any
                        cached data
group_means             Compute column-wise mean in X for each factor
                        level of Y
inverse_projection      Inverse of the Component Matrix
is_orthogonal           is it orthogonal
multiblock_biprojector
                        Create a Multiblock Bi-Projector
multiblock_projector    Create a Multiblock Projector
nblocks                 get the number of blocks
ncomp                   Get the number of components
nystrom_embedding       Nystrom method for out-of-sample embedding
partial_inverse_projection
                        Partial Inverse Projection of a Columnwise
                        Subset of Component Matrix
partial_project         Partially project a new sample onto subspace
partial_projector       Construct a partial projector
partial_projector.projector
                        construct a partial_projector from a
                        'projector' instance
pass                    a no-op pre-processing step
pca                     Principal Components Analysis (PCA)
perm_ci                 Permutation Confidence Intervals
predict.classifier      predict with a classifier object
prep                    prepare a dataset by applying a pre-processing
                        pipeline
prinang                 Compute principal angles for a set of subspaces
print.bi_projector      Pretty Print S3 Method for bi_projector Class
print.bi_projector_union
                        Pretty Print S3 Method for bi_projector_union
                        Class
print.classifier        Pretty Print Method for 'classifier' Objects
print.composed_projector
                        Pretty Print Method for 'composed_projector'
                        Objects
print.multiblock_biprojector
                        Pretty Print Method for
                        'multiblock_biprojector' Objects
print.projector         Pretty Print Method for 'projector' Objects
project                 New sample projection
project.cross_projector
                        project a cross_projector instance
project_block           Project a single "block" of data onto the
                        subspace
project_vars            Project one or more variables onto a subspace
projector               Construct a 'projector' instance
reconstruct             Reconstruct the data
refit                   refit a model
regress                 Multi-output linear regression
reprocess               apply pre-processing parameters to a new data
                        matrix
reprocess.cross_projector
                        reprocess a cross_projector instance
residualize             Compute a regression model for each column in a
                        matrix and return residual matrix
residuals               Obtain residuals of a component model fit
reverse_transform       reverse a pre-processing transform
rf_classifier           construct a random forest wrapper classifier
rf_classifier.projector
                        create a random forest classifier
rotate                  Rotate a Component Solution
scores                  Retrieve the component scores
sdev                    standard deviations
shape                   Shape of the Projector
shape.cross_projector   shape of a cross_projector instance
standardize             center and scale each vector of a matrix
std_scores              Compute standardized component scores
svd_wrapper             Singular Value Decomposition (SVD) Wrapper
transpose               Transpose a model
truncate                truncate a component fit
