{% set version = '2.9.0' %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/randomForestSRC_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/randomForestSRC/randomForestSRC_{{ version }}.tar.gz
  sha256: 9ce9ad6c51c0f8284efbac733063e31dbf162eec0ffda7a883e328c1ce9fbdcd

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

requirements:
  build:
    - {{ compiler('c') }}        # [not win]
    - {{native}}toolchain        # [win]
    - {{posix}}filesystem        # [win]
    - {{posix}}sed               # [win]
    - {{posix}}grep              # [win]
    - {{posix}}autoconf
    - {{posix}}automake          # [not win]
    - {{posix}}automake-wrapper  # [win]
    - {{posix}}pkg-config
    - {{posix}}make
    - {{posix}}coreutils         # [win]
    - {{posix}}zip               # [win]
  host:
    - r-base
  run:
    - r-base
    - {{native}}gcc-libs         # [win]

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

about:
  home: http://web.ccs.miami.edu/~hishwaran http://www.kogalur.com https://github.com/kogalur/randomForestSRC
  license: GPL (>= 3)
  summary: Fast OpenMP parallel computing of Breiman's random forests for survival, competing
    risks, regression and classification based on Ishwaran and Kogalur's popular random
    survival forests (RSF) package.  Handles missing data and now includes multivariate,
    unsupervised forests, quantile regression and solutions for class imbalanced data.  New
    fast interface using subsampling and confidence regions for variable importance.
  license_family: GPL3
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

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

# Package: randomForestSRC
# Version: 2.9.0
# Date: 2019-04-22
# Title: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
# Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Udaya B. Kogalur <ubk@kogalur.com>
# Maintainer: Udaya B. Kogalur <ubk@kogalur.com>
# BugReports: https://github.com/kogalur/randomForestSRC/issues/new
# Depends: R (>= 3.5.0),
# Imports: parallel
# Suggests: survival, pec, prodlim, mlbench, akima, caret, imbalance
# Description: Fast OpenMP parallel computing of Breiman's random forests for survival, competing risks, regression and classification based on Ishwaran and Kogalur's popular random survival forests (RSF) package.  Handles missing data and now includes multivariate, unsupervised forests, quantile regression and solutions for class imbalanced data.  New fast interface using subsampling and confidence regions for variable importance.
# License: GPL (>= 3)
# URL: http://web.ccs.miami.edu/~hishwaran http://www.kogalur.com https://github.com/kogalur/randomForestSRC
# NeedsCompilation: yes
# Packaged: 2019-04-22 15:31:10 UTC; kogalur
# Repository: CRAN
# Date/Publication: 2019-04-22 16:10:02 UTC
