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authorNaga Malleswari <nagamalli@riseup.net>2020-04-24 01:37:05 +0530
committerRicardo Wurmus <rekado@elephly.net>2020-04-24 15:51:39 +0200
commitaa3fdca85c6a28e8a945ac0041b921465fa0fb66 (patch)
tree44c5268f7f1c298c0283883d5e00a47b61c093e9 /gnu/packages/cran.scm
parentea43d299fa2071467cb1aec8cf3dc8f0d95b15f7 (diff)
downloadguix-aa3fdca85c6a28e8a945ac0041b921465fa0fb66.tar
guix-aa3fdca85c6a28e8a945ac0041b921465fa0fb66.tar.gz
gnu: Add r-sgloptim.
* gnu/packages/cran.scm (r-sgloptim): New variable. Signed-off-by: Ricardo Wurmus <rekado@elephly.net>
Diffstat (limited to 'gnu/packages/cran.scm')
-rw-r--r--gnu/packages/cran.scm36
1 files changed, 36 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index f0796891c8..d023c47705 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -21242,3 +21242,39 @@ Propagation-Separation approach to adaptive smoothing, the @dfn{Intersecting
Confidence Intervals} (ICI), variational approaches, and a non-local means
filter.")
(license license:gpl2+)))
+
+(define-public r-sgloptim
+ (package
+ (name "r-sgloptim")
+ (version "1.3.8")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "sglOptim" version))
+ (sha256
+ (base32
+ "15bkkvgp9v9vsp65wps48g3c2fa0fj1025hbrziywq14j7wayyjr"))))
+ (properties
+ `((upstream-name . "sglOptim")))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-bh" ,r-bh)
+ ("r-doparallel" ,r-doparallel)
+ ("r-foreach" ,r-foreach)
+ ("r-matrix" ,r-matrix)
+ ("r-rcpp" ,r-rcpp)
+ ("r-rcpparmadillo" ,r-rcpparmadillo)
+ ("r-rcppprogress" ,r-rcppprogress)))
+ (native-inputs
+ `(("r-knitr" ,r-knitr)))
+ (home-page "https://github.com/nielsrhansen/sglOptim")
+ (synopsis "Generic sparse group Lasso solver")
+ (description
+ "This package provides a fast generic solver for sparse group lasso
+optimization problems. The loss (objective) function must be defined in a C++
+module. The optimization problem is solved using a coordinate gradient
+descent algorithm. Convergence of the algorithm is established and the
+algorithm is applicable to a broad class of loss functions. Use of parallel
+computing for cross validation and subsampling is supported through the
+@code{foreach} and @code{doParallel} packages.")
+ (license license:gpl2+)))