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>.

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Description file content

Package
rsvd
Type
Package
Title
Randomized Singular Value Decomposition
Version
1.0.0
Date
2018-11-05
Author
N. Benjamin Erichson [aut, cre]
Maintainer
N. Benjamin Erichson
Description
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) .
Depends
R (>= 3.2.2)
Imports
Matrix
License
GPL (>= 3)
LazyData
TRUE
URL
BugReports
https://github.com/erichson/rSVD/issues
Suggests
ggplot2, testthat
RoxygenNote
6.1.0
NeedsCompilation
no
Packaged
2018-11-05 19:35:46 UTC; ben
Repository
CRAN
Date/Publication
2018-11-06 06:00:03 UTC

install.packages('rsvd')

1.0.0

11 days ago

https://github.com/erichson/rSVD

N. Benjamin Erichson

GPL (>= 3)

Depends on

R (>= 3.2.2)

Imports

Matrix

Suggests

ggplot2, testthat

Discussions