SPCAvRP: Sparse Principal Component Analysis via Random Projections
(SPCAvRP)
Implements the SPCAvRP algorithm, developed and analysed in "Sparse principal component analysis via random projections" Gataric, M., Wang, T. and Samworth, R. J. (2018) <arXiv:1712.05630>. The algorithm is based on the aggregation of eigenvector information from carefully-selected random projections of the sample covariance matrix.
| Version: |
0.4 |
| Depends: |
R (≥ 3.0.0), parallel, MASS |
| Published: |
2019-05-03 |
| Author: |
Milana Gataric, Tengyao Wang and Richard J. Samworth |
| Maintainer: |
Milana Gataric <m.gataric at statslab.cam.ac.uk> |
| License: |
GPL-3 |
| URL: |
https://arxiv.org/abs/1712.05630 |
| NeedsCompilation: |
no |
| CRAN checks: |
SPCAvRP results |
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