{% set version = "0.6.7" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/LambertW_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/LambertW/LambertW_{{ version }}.tar.gz
  sha256: 9846099ac238640b4af4669b136b0c2091b49ff59ab5c08c6fc236ca04314d95

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

requirements:
  build:
    - {{ compiler('c') }}              # [not win]
    - {{ compiler('m2w64_c') }}        # [win]
    - {{ compiler('cxx') }}            # [not win]
    - {{ compiler('m2w64_cxx') }}      # [win]
    - {{ posix }}filesystem        # [win]
    - {{ posix }}make
    - {{ posix }}sed               # [win]
    - {{ posix }}coreutils         # [win]
    - {{ posix }}zip               # [win]
  host:
    - r-base
    - r-mass
    - r-rcolorbrewer
    - r-rcpp >=1.0.4
    - r-ggplot2
    - r-lamw >=1.3.0
    - r-reshape2
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-mass
    - r-rcolorbrewer
    - r-rcpp >=1.0.4
    - r-ggplot2
    - r-lamw >=1.3.0
    - r-reshape2

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

about:
  home: https://github.com/gmgeorg/LambertW http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265 http://arxiv.org/abs/1602.02200
  license: GPL-2.0-or-later
  summary: "Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed\
    \ RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. Probably the most important function is 'Gaussianize', which works similarly to 'scale',\
    \ but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x 'MyFavoriteDistribution' and use it in their analysis right away."
  license_family: GPL2
  license_file:
    - {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2

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

# Package: LambertW
# Type: Package
# Title: Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data
# Version: 0.6.5
# Date: 2020-06-06
# Authors@R: person(given = "Georg M.", family = "Goerg", role = c("aut", "cre"), email = "im@gmge.org")
# URL: https://github.com/gmgeorg/LambertW http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265 http://arxiv.org/abs/1602.02200
# Description: Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. Probably the most important function is 'Gaussianize', which works similarly to 'scale', but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x 'MyFavoriteDistribution' and use it in their analysis right away.
# Depends: MASS, ggplot2,
# Imports: lamW (>= 1.3.0), stats, graphics, grDevices, RColorBrewer, reshape2, Rcpp (>= 1.0.4), methods
# Suggests: boot, Rsolnp, nortest, numDeriv, testthat, data.table, moments, knitr, vars,
# License: GPL (>= 2)
# LazyLoad: yes
# NeedsCompilation: yes
# Repository: CRAN
# LinkingTo: Rcpp, lamW
# RoxygenNote: 7.1.0
# Encoding: UTF-8
# VignetteBuilder: knitr
# Packaged: 2020-06-07 22:12:20 UTC; georg
# Author: Georg M. Goerg [aut, cre]
# Maintainer: Georg M. Goerg <im@gmge.org>
# Date/Publication: 2020-06-08 06:10:02 UTC
