apca: 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>.
| Version: |
1.0.0 |
| Imports: |
stats |
| Published: |
2026-04-28 |
| DOI: |
10.32614/CRAN.package.apca |
| Author: |
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) |
| Maintainer: |
Angga Dwi Mulyanto <angga.dwi.m at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
NEWS |
| CRAN checks: |
apca results |
Documentation:
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