{% set version = '2.15.2' %}

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

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/qgcomp_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/qgcomp/qgcomp_{{ version }}.tar.gz
  sha256: 57c79c9297cab8cc7e83dab8cf0e3e227f537e71431e2bf91ca6d5fa0bcc9462

build:
  merge_build_host: True  # [win]
  # If this is a new build for the same version, increment the build number.
  number: 0
  # no skip
  noarch: generic

  # This is required to make R link correctly on Linux.
  rpaths:
    - lib/R/lib/
    - lib/

# Suggests: broom, devtools, knitr, markdown, MASS, mice
requirements:
  build:
    - {{ posix }}zip               # [win]

  host:
    - r-base
    - r-arm
    - r-future
    - r-future.apply
    - r-generics
    - r-ggplot2 >=3.3.0
    - r-gridextra
    - r-nnet
    - r-pscl
    - r-survival
    - r-tibble

  run:
    - r-base
    - r-arm
    - r-future
    - r-future.apply
    - r-generics
    - r-ggplot2 >=3.3.0
    - r-gridextra
    - r-nnet
    - r-pscl
    - r-survival
    - r-tibble

test:
  commands:
    # You can put additional test commands to be run here.
    - $R -e "library('qgcomp')"           # [not win]
    - "\"%R%\" -e \"library('qgcomp')\""  # [win]

  # You can also put a file called run_test.py, run_test.sh, or run_test.bat
  # in the recipe that will be run at test time.

  # requires:
    # Put any additional test requirements here.

about:
  home: https://github.com/alexpkeil1/qgcomp/
  license: GPL-2
  summary: 'G-computation for a set of time-fixed exposures with quantile-based basis functions,
    possibly under linearity and homogeneity assumptions. This approach estimates a
    regression line corresponding to the expected change in the outcome (on the link
    basis) given a simultaneous increase in the quantile-based category for all exposures.
    Works with continuous, binary, and right-censored time-to-event outcomes.  Reference:
    Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan
    Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing
    the effects of exposure mixtures; <doi:10.1289/EHP5838>.'
  license_family: GPL2
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2'

# The original CRAN metadata for this package was:

# Package: qgcomp
# Title: Quantile G-Computation
# Version: 2.15.2
# Date: 2023-08-09
# Authors@R: person("Alexander", "Keil", , "alex.keil@nih.gov", role = c("aut", "cre"))
# Description: G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. This approach estimates a regression line corresponding to the expected change in the outcome (on the link basis) given a simultaneous increase in the quantile-based category for all exposures. Works with continuous, binary, and right-censored time-to-event outcomes.  Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; <doi:10.1289/EHP5838>.
# License: GPL (>= 2)
# URL: https://github.com/alexpkeil1/qgcomp/
# BugReports: https://github.com/alexpkeil1/qgcomp/issues
# Depends: R (>= 3.5.0)
# Imports: arm, future, future.apply, generics, ggplot2 (>= 3.3.0), grDevices, grid, gridExtra, nnet, pscl, stats, survival, tibble
# Suggests: broom, devtools, knitr, markdown, MASS, mice
# VignetteBuilder: knitr
# Encoding: UTF-8
# Language: en-US
# RoxygenNote: 7.2.3
# NeedsCompilation: no
# Packaged: 2023-08-09 05:04:04 UTC; keilap
# Author: Alexander Keil [aut, cre]
# Maintainer: Alexander Keil <alex.keil@nih.gov>
# Repository: CRAN
# Date/Publication: 2023-08-10 09:10:06 UTC

# See
# https://docs.conda.io/projects/conda-build for
# more information about meta.yaml
