r-cran-rsvd 1.0.3-3build1 source package in Ubuntu
Changelog
r-cran-rsvd (1.0.3-3build1) groovy; urgency=medium * No-change rebuild against r-api-4.0 -- Graham Inggs <email address hidden> Sat, 30 May 2020 16:47:09 +0000
Upload details
- Uploaded by:
- Graham Inggs
- Uploaded to:
- Groovy
- Original maintainer:
- Debian R Packages Maintainers
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| r-cran-rsvd_1.0.3.orig.tar.gz | 3.3 MiB | 13560e0fc3ae6927c4cc4d5ad816b1f640a2a445b712a5a612ab17ea0ce179bb |
| r-cran-rsvd_1.0.3-3build1.debian.tar.xz | 3.9 KiB | e34161e7eca54601dccb53558071f7b2aedd1e806ad792b218b9f998234080fb |
| r-cran-rsvd_1.0.3-3build1.dsc | 2.1 KiB | 83019eed275aa384429b7e90c738193c5fb9b140e26f376c6571e84b1ae7b37b |
Available diffs
- diff from 1.0.3-3 (in Debian) to 1.0.3-3build1 (306 bytes)
Binary packages built by this source
- r-cran-rsvd: Randomized Singular Value Decomposition
Low-rank matrix decompositions are fundamental tools and widely used for
data analysis, dimension reduction, and data compression. Classically,
highly accurate deterministic matrix algorithms are used for this task.
However, the emergence of large-scale data has severely challenged our
computational ability to analyze big data. The concept of randomness has
been demonstrated as an effective strategy to quickly produce
approximate answers to familiar problems such as the singular value
decomposition (SVD). The rsvd package provides several randomized matrix
algorithms such as the randomized singular value decomposition (rsvd),
randomized principal component analysis (rpca), randomized robust
principal component analysis (rrpca), randomized interpolative
decomposition (rid), and the randomized CUR decomposition (rcur). In
addition several plot functions are provided. The methods are discussed
in detail by Erichson et al. (2016) <arXiv:1608.02148>.
