bucket_AC/R-glmnet

   1 # Buildsheet autogenerated by ravenadm tool -- Do not edit.
   2
   3 NAMEBASE=               R-glmnet
   4 VERSION=                4.1-8
   5 KEYWORDS=               cran
   6 VARIANTS=               std
   7 SDESC[std]=             Generalized Linear Models for Lasso, etc
   8 HOMEPAGE=               https://glmnet.stanford.edu
   9 CONTACT=                CRAN_Automaton[cran@ironwolf.systems]
  10
  11 DOWNLOAD_GROUPS=        main
  12 SITES[main]=            CRAN/src/contrib
  13                         https://loki.dragonflybsd.org/cranfiles/
  14 DISTFILE[1]=            glmnet_4.1-8.tar.gz:main
  15 DIST_SUBDIR=            CRAN
  16 DF_INDEX=               1
  17 SPKGS[std]=             single
  18
  19 OPTIONS_AVAILABLE=      none
  20 OPTIONS_STANDARD=       none
  21
  22 BUILDRUN_DEPENDS=       R-foreach:single:std
  23                         R-shape:single:std
  24                         R-Rcpp:single:std
  25                         R-RcppEigen:single:std
  26
  27 USES=                   cran gmake gettext:build
  28
  29 DISTNAME=               glmnet
  30
  31 GENERATED=              yes
  32
  33 INSTALL_REQ_TOOLCHAIN=  yes
  34
  35 [FILE:1104:descriptions/desc.single]
  36 glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models
  37
  38 Extremely efficient procedures for fitting the entire lasso or elastic-net
  39 regularization path for linear regression, logistic and multinomial
  40 regression models, Poisson regression, Cox model, multiple-response
  41 Gaussian, and the grouped multinomial regression; see &lt;<a
  42 href="https://doi.org/10.18637%2Fjss.v033.i01"
  43 target="_top">doi:10.18637/jss.v033.i01</a>&gt; and &lt;<a
  44 href="https://doi.org/10.18637%2Fjss.v039.i05"
  45 target="_top">doi:10.18637/jss.v039.i05</a>&gt;. There are two new and
  46 important additions. The family argument can be a GLM family object, which
  47 opens the door to any programmed family (&lt;<a
  48 href="https://doi.org/10.18637%2Fjss.v106.i01"
  49 target="_top">doi:10.18637/jss.v106.i01</a>&gt;). This comes with a modest
  50 computational cost, so when the built-in families suffice, they should be
  51 used instead. The other novelty is the relax option, which refits each of
  52 the active sets in the path unpenalized. The algorithm uses cyclical
  53 coordinate descent in a path-wise fashion, as described in the papers
  54 cited.
  55
  56
  57 [FILE:103:distinfo]
  58 1ddbe5ce07076d1bdf58b0202ebd0ceac8eeb4796c5175681adb9e58c30ddcfe      2439515 CRAN/glmnet_4.1-8.tar.gz
  59