39 lines
1.9 KiB
Python
39 lines
1.9 KiB
Python
# Copyright 2013-2024 Lawrence Livermore National Security, LLC and other
|
|
# Spack Project Developers. See the top-level COPYRIGHT file for details.
|
|
#
|
|
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
|
|
|
|
from spack.package import *
|
|
|
|
|
|
class RGlmnet(RPackage):
|
|
"""Lasso and Elastic-Net Regularized Generalized Linear Models.
|
|
|
|
Extremely efficient procedures for fitting the entire lasso or elastic-net
|
|
regularization path for linear regression, logistic and multinomial
|
|
regression models, Poisson regression and the Cox model. Two recent
|
|
additions are the multiple-response Gaussian, and the grouped multinomial.
|
|
The algorithm uses cyclical coordinate descent in a path-wise fashion, as
|
|
described in the paper linked to via the URL below."""
|
|
|
|
cran = "glmnet"
|
|
|
|
license("GPL-2.0-only")
|
|
|
|
version("4.1-7", sha256="b3a0b606d99df0256eb68e6ebd271e071b246900a4379641af2e7d548c70eaa8")
|
|
version("4.1-4", sha256="f6b0f70a0b3d81ff91c2b94f795a2a32e90dd458270f1a29e49e085dd65000f9")
|
|
version("4.1-3", sha256="64bc35aa40b6e580cfb8a21e649eb103e996e8747a10c476b8bb9545c846325a")
|
|
version("4.1", sha256="8f0af50919f488789ecf261f6e0907f367d89fca812baa2f814054fb2d0e40cb")
|
|
version("2.0-18", sha256="e8dce9d7b8105f9cc18ba981d420de64a53b09abee219660d3612915d554256b")
|
|
version("2.0-13", sha256="f3288dcaddb2f7014d42b755bede6563f73c17bc87f8292c2ef7776cb9b9b8fd")
|
|
version("2.0-5", sha256="2ca95352c8fbd93aa7800f3d972ee6c1a5fcfeabc6be8c10deee0cb457fd77b1")
|
|
|
|
depends_on("r@3.6.0:", type=("build", "run"), when="@4.1:")
|
|
|
|
depends_on("r-matrix@1.0-6:", type=("build", "run"))
|
|
depends_on("r-foreach", type=("build", "run"))
|
|
depends_on("r-shape", type=("build", "run"), when="@4.1:")
|
|
depends_on("r-survival", type=("build", "run"), when="@4.1:")
|
|
depends_on("r-rcpp", type=("build", "run"), when="@4.1-3:")
|
|
depends_on("r-rcppeigen", type=("build", "run"), when="@4.1-3:")
|