The RSCA provides the following functions for performing regularized SCA.
A DISCO-SCA procedure for identifying common and distinctive components.
Tucker's coefficient of congruence between columns but after accounting for permutational freedom and reflections.
Proportion of variance accounted for (VAF) for each block and each principal component.
A K-fold cross-validation procedure when common/distinctive processes are unknown with Lasso and Group Lasso penalties.
A K-fold cross-validation procedure when common/distinctive processes are known, with a Lasso penalty.
An algorithm for determining the smallest values for Lasso and Group Lasso tuning parameters that yield all zeros.
Standardize the given data matrix per column, over the rows.
PCA-GCA method for selecting the number of common and distinctive components.
Variable selection with Lasso and Group Lasso with a multi-start procedure.
Variable selection algorithm with a predefined component loading structure.
Undo shrinkage (on estimated component loading matrix).
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