{% set version = '1.23' %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/logistf_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/logistf/logistf_{{ version }}.tar.gz
  sha256: 5adb22a40569883395dc048c877f849dd08d07582a991f1b160f0338f0b13838

build:
  merge_build_host: True  # [win]
  number: 2
  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-mgcv
    - r-mice
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-mgcv
    - r-mice

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

about:
  home: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/fllogistf/
  license: GPL
  summary: Fit a logistic regression model using Firth's bias reduction method, equivalent to
    penalization of the log-likelihood by the Jeffreys  prior. Confidence intervals
    for regression coefficients can be computed by penalized profile likelihood. Firth's
    method was proposed as ideal solution to the problem of separation in logistic regression.
    If needed, the bias reduction can be turned off such that ordinary maximum likelihood
    logistic regression is obtained.
  license_family: GPL
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

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

# Package: logistf
# Version: 1.23
# Date: 2018-07-19
# Title: Firth's Bias-Reduced Logistic Regression
# Authors@R: c(person("Georg", "Heinze", role=c("aut", "cre"), email="georg.heinze@meduniwien.ac.at"), person("Meinhard", "Ploner", role=c("aut")), person("Daniela","Dunkler", role=c("ctb")), person("Harry", "Southworth", role=c("ctb")))
# Depends: R (>= 3.0.0)
# Imports: mice, mgcv
# Description: Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys  prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal solution to the problem of separation in logistic regression. If needed, the bias reduction can be turned off such that ordinary maximum likelihood logistic regression is obtained.
# License: GPL
# URL: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/fllogistf/
# LazyLoad: yes
# NeedsCompilation: yes
# Packaged: 2018-07-19 15:57:04 UTC; Biometrikus
# Author: Georg Heinze [aut, cre], Meinhard Ploner [aut], Daniela Dunkler [ctb], Harry Southworth [ctb]
# Maintainer: Georg Heinze <georg.heinze@meduniwien.ac.at>
# Repository: CRAN
# Date/Publication: 2018-07-19 17:40:10 UTC
