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-rw-r--r--gnu/packages/cran.scm32
1 files changed, 32 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index 7e2539da81..82fd465d79 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -10618,3 +10618,35 @@ the local machine to, say, distributed processing on a remote compute cluster.")
can be resolved using any future-supported backend, e.g. parallel on the local
machine or distributed on a compute cluster.")
(license license:gpl2+)))
+
+(define-public r-rsvd
+ (package
+ (name "r-rsvd")
+ (version "1.0.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "rsvd" version))
+ (sha256
+ (base32
+ "0vjhrvnkl9rmvl8sv2kac5sd10z3fgxymb676ynxzc2pmhydy3an"))))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-matrix" ,r-matrix)))
+ (home-page "https://github.com/erichson/rSVD")
+ (synopsis "Randomized singular value decomposition")
+ (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 @dfn{singular value decomposition} (SVD). This package
+provides several randomized matrix algorithms such as the randomized singular
+value decomposition (@code{rsvd}), randomized principal component
+analysis (@code{rpca}), randomized robust principal component
+analysis (@code{rrpca}), randomized interpolative decomposition (@code{rid}),
+and the randomized CUR decomposition (@code{rcur}). In addition several plot
+functions are provided.")
+ (license license:gpl3+)))