{% set version = "5.3-2" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

package:
  name: r-gamlss.dist
  version: {{ version|replace("-", "_") }}

source:
  url:
    - {{ cran_mirror }}/src/contrib/gamlss.dist_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/gamlss.dist/gamlss.dist_{{ version }}.tar.gz
  sha256: 0caa92cd20c3d2d11b1af4656fd0de09adf145992345cba07fdcd33b7716ced3

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-mass
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-mass

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

about:
  home: http://www.gamlss.org/
  license: GPL-2.0-or-later
  summary: "A set of distributions  which can be used  for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed  distributions.  Extra distributions can be\
    \ created, by transforming, any continuous distribution defined on the real line,  to  a distribution defined on ranges 0 to infinity  or  0 to 1,  by using a ''log'' or a ''logit' transformation respectively. "
  license_family: GPL3
  license_file:
    - {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2

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

# Package: gamlss.dist
# Type: Package
# Title: Distributions for Generalized Additive Models for Location Scale and Shape
# Version: 5.1-4
# Date: 2019-5-14
# Authors@R: c(person("Mikis", "Stasinopoulos", role = c("aut", "cre", "cph"),  email = "d.stasinopoulos@londonmet.ac.uk"), person("Robert", "Rigby", role = c("aut"), email = "r.rigby@londonmet.ac.uk"),  person("Calliope", "Akantziliotou", role = "ctb"), person("Vlasios", "Voudouris", role = "ctb"), person("Gillian", "Heller", role = "ctb"), person("Fernanda", "De Bastiani", role = "ctb"), person("Raydonal", "Ospina", role = "ctb", email= "rospina@ime.usp.br"), person("Nicoletta", "Motpan", role = "ctb"), person("Fiona", "McElduff", role = "ctb"), person("Majid", "Djennad", role = "ctb"), person("Marco", "Enea", role = "ctb"), person("Alexios", "Ghalanos", role = "ctb"), person("Christos", "Argyropoulos", role = "ctb"), person("Almond", "Stocker", role = "ctb"), person("Jens", "Lichter", role = "ctb"), person("Stanislaus", "Stadlmann", role = "ctb")      )
# Description: A set of distributions  which can be used  for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed  distributions.  Extra distributions can be created, by transforming, any continuous distribution defined on the real line,  to  a distribution defined on ranges 0 to infinity  or  0 to 1,  by using a ''log'' or a ''logit' transformation respectively.
# License: GPL-2 | GPL-3
# URL: http://www.gamlss.org/
# Depends: R (>= 2.15.0), MASS, graphics, stats, methods, grDevices
# Repository: CRAN
# Author: Mikis Stasinopoulos [aut, cre, cph], Robert Rigby [aut], Calliope Akantziliotou [ctb], Vlasios Voudouris [ctb], Gillian Heller [ctb], Fernanda De Bastiani [ctb], Raydonal Ospina [ctb], Nicoletta Motpan [ctb], Fiona McElduff [ctb], Majid Djennad [ctb], Marco Enea [ctb], Alexios Ghalanos [ctb], Christos Argyropoulos [ctb], Almond Stocker [ctb], Jens Lichter [ctb], Stanislaus Stadlmann [ctb]
# Maintainer: Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>
# NeedsCompilation: yes
# Packaged: 2019-05-14 08:52:38 UTC; MikisStasinopoulos
# Date/Publication: 2019-05-15 10:00:09 UTC
