Advanced Principal Component Analysis // Provides nine computational algorithms for dimensionality reduction via Principal Component Analysis (PCA), built using an object- oriented (S3) architecture. The package includes classical and modern methods: Singular Value Decomposition (SVD) based on Eckart and Young (1936) doi:10.1007/BF02288367, Power Iteration based on Hotelling (1933) doi:10.1037/h0071325, QR Algorithm based on Francis (1961) doi:10.1093/comjnl/4.3.265, Jacobi Algorithm based on Jacobi (1846) doi:10.1515/crll.1846.30.51, Arnoldi Iteration based on Arnoldi (1951) doi:10.1090/qam/42792, 'NIPALS' based on Wold (1975) doi:10.1017/S0021900200047604, Alternating Least Squares (ALS) based on Kolda and Bader (2009) doi:10.1137/07070111X, Probabilistic PCA (PPCA) with EM Algorithm based on Tipping and Bishop (1999) doi:10.1111/1467-9868.00196, and Generalized Hebbian Algorithm (GHA) based on Sanger (1989) doi:10.1016/0893-6080(89)90044-0.