Sparse Principal Component Analysis with Multiple Principal Components
Fraction of variance explained per PC
Fraction of variance explained
Multiple Sparse PCA
Orthogonality constraint violation
Pairwise correlation
Print mspca output
Truncated Power Method
Variance explained per PC
Implements an algorithm for computing multiple sparse principal components of a dataset. The method is based on Cory-Wright and Pauphilet "Sparse PCA with Multiple Principal Components" (2022) <doi:10.48550/arXiv.2209.14790>. The algorithm uses an iterative deflation heuristic with a truncated power method applied at each iteration to compute sparse principal components with controlled sparsity.