{% set version = "3.4.0" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

package:
  name: r-grpreg
  version: {{ version|replace("-", "_") }}

source:
  url:
    - {{ cran_mirror }}/src/contrib/grpreg_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/grpreg/grpreg_{{ version }}.tar.gz
  sha256: fd57d20baf63d2cc5821998bca5c3fdcbe46c933c9553caa492911b12654d6ad

build:
  merge_build_host: true  # [win]
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/

requirements:
  build:
    - {{ compiler('c') }}        # [not win]
    - {{ compiler('m2w64_c') }}        # [win]
    - {{ posix }}filesystem        # [win]
    - {{ posix }}make
    - {{ posix }}sed               # [win]
    - {{ posix }}coreutils         # [win]
    - {{ posix }}zip               # [win]
  host:
    - r-base
    - r-matrix
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-matrix

test:
  commands:
    - $R -e "library('grpreg')"           # [not win]
    - "\"%R%\" -e \"library('grpreg')\""  # [win]

about:
  home: http://pbreheny.github.io/grpreg, https://github.com/pbreheny/grpreg
  license: GPL-3.0-only
  summary: Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties.  This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP,
    and the group bridge.
  license_family: GPL3
  license_file: {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3

extra:
  recipe-maintainers:
    - conda-forge/r

# Package: grpreg
# Title: Regularization Paths for Regression Models with Grouped Covariates
# Version: 3.2-1
# Date: 2019-02-26
# Authors@R: c( person("Patrick", "Breheny", role=c("aut","cre"), email="patrick-breheny@uiowa.edu", comment=c(ORCID="000-0002-0650-1119")), person("Yaohui", "Zeng", role="ctb"))
# Depends: R (>= 3.1.0)
# Imports: Matrix
# Suggests: grpregOverlap, knitr, survival
# VignetteBuilder: knitr
# Description: Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties.  This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.
# BugReports: http://github.com/pbreheny/grpreg/issues
# License: GPL-3
# URL: http://pbreheny.github.io/grpreg, https://github.com/pbreheny/grpreg
# LazyData: TRUE
# RoxygenNote: 6.1.1
# NeedsCompilation: yes
# Packaged: 2019-02-26 21:05:37 UTC; pbreheny
# Author: Patrick Breheny [aut, cre] (<https://orcid.org/000-0002-0650-1119>), Yaohui Zeng [ctb]
# Maintainer: Patrick Breheny <patrick-breheny@uiowa.edu>
# Repository: CRAN
# Date/Publication: 2019-02-26 21:40:03 UTC
