Regularized Simultaneous Component Based Data Integration


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Documentation for package ‘RegularizedSCA’ version 0.5.0

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RSCA-package RSCA: A package for regularized simultaneous component analysis (SCA) for data integration.
cv_sparseSCA A K-fold cross-validation procedure when common/distinctive processes are unknown with Lasso and Group Lasso penalties.
cv_structuredSCA A K-fold cross-validation procedure when common/distinctive processes are known, with a Lasso penalty.
DISCOsca DISCO-SCA rotation.
Herring Herring data
maxLGlasso An algorithm for determining the smallest values for Lasso and Group Lasso tuning parameters that yield all zeros.
mySTD Standardize the given data matrix per column, over the rows.
pca_gca PCA-GCA method for selecting the number of common and distinctive components.
plot.CVsparseSCA Ploting Cross-validation results
plot.CVstructuredSCA Cross-validation plot
RSCA RSCA: A package for regularized simultaneous component analysis (SCA) for data integration.
sparseSCA Variable selection with Lasso and Group Lasso with a multi-start procedure.
structuredSCA Variable selection algorithm with a predefined component loading structure.
summary.CVsparseSCA Display a summary of the results of 'cv_sparseSCA()'.
summary.CVstructuredSCA Display a summary of the results of 'cv_structuredSCA()'.
summary.DISCOsca Display a summary of the results of 'DISCOsca()'.
summary.sparseSCA Display a summary of the results of 'sparseSCA()'.
summary.structuredSCA Display a summary of the results of 'structuredSCA()'.
summary.undoS Display a summary of the results of 'undoShrinkage()'.
summary.VAF Display a summary of the results of 'VAF()'.
TuckerCoef Tucker coefficient of congruence.
undoShrinkage Undo shrinkage.
VAF Proportion of variance accounted for (VAF) for each block and each principal component.