Advanced Principal Component Analysis R package apca version 1.0.0 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>. Software Imports: stats Angga Dwi Mulyanto <angga.dwi.m@gmail.com> Comprehensive R Archive Network (CRAN) Angga Dwi Mulyanto [aut, cre] (Institut Teknologi Sepuluh Nopember, Universitas Islam Negeri Maulana Malik Ibrahim Malang), Bambang Widjanarko Otok [aut] (Institut Teknologi Sepuluh Nopember), Jerry Dwi Trijoyo Purnomo [aut] (Institut Teknologi Sepuluh Nopember) MIT + file LICENSE (https://CRAN.R-project.org/package=apca/LICENSE) 2026-04-28 application/tgz https://CRAN.R-project.org/package=apca doi:10.32614/CRAN.package.apca en-US