Generalized Principal Component Analysis is a methodological framework in multivariate statistics that extends classical Principal Component Analysis by modeling data as arising from multiple subspaces or nonlinear structures, thereby enabling dimensionality reduction and data representation in the presence of heterogeneous or non-Gaussian underlying patterns.
95
Publications
11.1K
Citations
223
Authors
118
Institutions
Publications per year
2017–2026
21
Parents
Publications
95
Nonlinear Multivariate Analysis.
M.O. Hill, A. Gifi · Journal of Ecology · 1990 · 910 citations
Canonical analysis of several sets of variables
J. R. Kettenring · Biometrika · 1971 · 786 citations
1–5 of 95
Authors
223
- MF
4
h-index
- ML
4
h-index
- AGA. Gifi
3 publications · 1.6K citations
3
h-index
- RC
3
h-index
- GV
3
h-index
1–5 of 223
Institutions
118
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
9 publications
1.9K citations
University of Modena and Reggio Emilia
Modena, Italy
4 h-index
4 publications
630 citations
Bank of Italy
Rome, Italy
3 h-index
6 publications
1.2K citations
Nanyang Technological University
Singapore, Singapore
3 h-index
11 publications
1.2K citations
University of Pennsylvania
Philadelphia, United States
3 h-index
5 publications
487 citations
Institute for Infocomm Research
Singapore, Singapore
3 h-index
6 publications
789 citations
University of California, Davis
Davis, United States
2 h-index
2 publications
235 citations
City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
2 publications
50 citations
1–8 of 118
Venues
- Pattern Recognition
4 publications · 221 citations
4
h-index
- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 3 publications · 1.4K citations
3
h-index
- Computational Statistics & Data Analysis
CSDA · 3 publications · 206 citations
3
h-index
- arXiv (Cornell University)
Repository · 3 publications · 44 citations
3
h-index
- Journal of Multivariate Analysis
3 publications · 154 citations
3
h-index
1–5