irlba v2.3.3
0
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Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices
Fast and memory efficient methods for truncated singular value
decomposition and principal components analysis of large sparse and dense
matrices.
Functions in irlba
| Name | Description | |
| summary.irlba_prcomp | Summary method for truncated pca objects computed by prcomp_irlba. | |
| ssvd | Sparse regularized low-rank matrix approximation. | |
| prcomp_irlba | Principal Components Analysis | |
| svdr | Find a few approximate largest singular values and corresponding singular vectors of a matrix. | |
| partial_eigen | Find a few approximate largest eigenvalues and corresponding eigenvectors of a symmetric matrix. | |
| irlba | Find a few approximate singular values and corresponding singular vectors of a matrix. | |
| No Results! | ||
Vignettes of irlba
| Name | ||
| irlba.Rnw | ||
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2019-02-04 |
| LinkingTo | Matrix |
| License | GPL-3 |
| BugReports | https://github.com/bwlewis/irlba/issues |
| RoxygenNote | 5.0.1 |
| NeedsCompilation | yes |
| Packaged | 2019-02-05 14:03:24 UTC; blewis |
| Repository | CRAN |
| Date/Publication | 2019-02-05 14:53:31 UTC |
| depends | Matrix |
| imports | methods , stats |
| Contributors | Jim Baglama, Lothar Reichel |
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