r-cran-rsvd 1.0.2-1 source package in Ubuntu

Changelog

r-cran-rsvd (1.0.2-1) unstable; urgency=medium

  * Initial release (closes: #934653)

 -- Steffen Moeller <email address hidden>  Mon, 12 Aug 2019 15:04:59 +0200

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Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

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Series Pocket Published Component Section

Builds

Eoan: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-rsvd_1.0.2-1.dsc 2.0 KiB ed6f0fd51355c3a2b11d90699cf032a534e5112814eda1c0cdcca3cc981143d2
r-cran-rsvd_1.0.2.orig.tar.gz 3.3 MiB c8fe5c18bf7bcfe32604a897e3a7caae39b49e47e93edad9e4d07657fc392a3a
r-cran-rsvd_1.0.2-1.debian.tar.xz 3.3 KiB 7b5addcc87c667a001d5b90879da829717398157fe205ef78eaa0cbd84d55e67

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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>.