multivarious0.3.1 package

Add a pre-processing node to a pipeline

add a pre-processing stage

Apply rotation

apply a pre-processing transform

A Union of Concatenated bi_projector Fits

Construct a bi_projector instance

Biplot for PCA Objects (Enhanced with ggrepel)

Extract the Block Indices from a Multiblock Projector

get block_indices

get block_lengths

Fast, Exact Bootstrap for PCA Results from pca function

Bootstrap inference for PLSC loadings

Bootstrap Resampling for Multivariate Models

center a data matrix

Check if preprocessor is fitted and error if not

Create a k-NN classifier for a discriminant projector

Multiblock Bi-Projector Classifier

Construct a Classifier

Get Coefficients of a Composed Projector

Extract coefficients from a cross_projector object

Coefficients for a Multiblock Projector

scale a data matrix

get the components

Compose Multiple Partial Projectors

Compose Two Projectors

bind together blockwise pre-processors

Contrastive PCA++ (cPCA++) Performs Contrastive PCA++ (cPCA++) to find...

Partial Least Squares Correlation (PLSC)

Predict Class Labels using a Classifier Object

Two-way (cross) projection to latent components

Generic cross-validation engine

Cross-validation Framework

Construct a Discriminant Projector

Construct a partial projector

a no-op pre-processing step

PCA Outlier Diagnostics

Principal Components Analysis (PCA)

Permutation Confidence Intervals

Permutation test for PLSC latent variables

Generic Permutation-Based Test

Predict method for a discriminant_projector, supporting LDA or Euclid

Project a single "block" of data onto the subspace

Project one or more variables onto a subspace

project a cross_projector instance

Project new data using a Nyström approximation model

New sample projection

Construct a projector instance

Calculate Rank Score for Predictions

Reconstruct new data in a model's subspace

Reconstruct Data from Scores using a Composed Projector

Reconstruct Data from PCA Results

Reconstruct the data

Reconstruct fitted or subsetted outputs for a regress object

refit a model

Multi-output linear regression

reprocess a cross_projector instance

Reprocess data for Nyström approximation

apply pre-processing parameters to a new data matrix

Compute a regression model for each column in a matrix and return resi...

Obtain residuals of a component model fit

reverse a pre-processing transform

Create a random forest classifier

construct a random forest wrapper classifier

Possibly use ridge-regularized inversion of crossprod(v)

Rotate PCA Loadings

Rotate a Component Solution

Extract scores from a PLSC fit

Retrieve the component scores

Screeplot for PCA

Screeplot for PCA

standard deviations

shape of a cross_projector instance

Shape of the Projector

center and scale each vector of a matrix

Compute standardized component scores

Calculate Standardized Scores for SVD results

Compute subspace similarity

Summarize a Composed Projector

Singular Value Decomposition (SVD) Wrapper

top-k accuracy indicator

Transfer from X domain to Y domain (or vice versa) in a cross_projecto...

Transfer data from one domain/block to another via a latent space

Transform data using a fitted preprocessing pipeline

Transpose a model

Truncate a Composed Projector

truncate a component fit

Identify Original Variables Used by a Projector

Identify Original Variables for a Specific Component

Create a Multiblock Projector

get the number of blocks

Get the number of components

Nyström approximation for kernel-based decomposition (Unified Version)

Partially project a new sample onto subspace

Print Method for PCA Objects

Print Method for perm_test_pca Objects

Print Method for perm_test Objects

Print a pre_processor object

Print a prepper pipeline

Pretty Print Method for regress Objects

Pretty Print Method for rf_classifier Objects

Project Data onto a Specific Block

Default inverse_projection method for cross_projector

Inverse of the Component Matrix

Inverse transform data using a fitted preprocessing pipeline

Check if a preprocessing object is fitted

Stricter check for true orthogonality

is it orthogonal

Enhanced fitted state tracking

Compute inter-block transfer error metrics for a cross_projector

Compute reconstruction-based error metrics

Create a Multiblock Bi-Projector

Evaluate Feature Importance for a Classifier

Evaluate feature importance

Fit and transform data in one step

Fit a preprocessing pipeline

Get a fresh pre-processing node cleared of any cached data

Generalized Eigenvalue Decomposition

Get fitted state from attributes

Compute column-wise mean in X for each factor level of Y

initialize a transform

Compute the Inverse Projection for a Composed Projector

Partial Inverse Projection of a Subset of the Loading Matrix in cross_...

Partial Inverse Projection of a Columnwise Subset of Component Matrix

Partial Inverse Projection for a regress Object

Partial Project Through a Composed Partial Projector

Partially project data for a cross_projector

Predict Class Labels using a Random Forest Classifier Object

prepare a dataset by applying a pre-processing pipeline

Convenience function for preprocessing workflow

Calculate Principal Angles Between Subspaces

Principal angles (two sub‑spaces)

Pretty Print S3 Method for bi_projector Class

Print method for bootstrap_pca_result

Pretty Print Method for classifier Objects

Print a concat_pre_processor object

Pretty Print Method for multiblock_biprojector Objects