# This file created by conda-build 2.1.17
# meta.yaml template originally from:
# C:\projects\r-aod-feedstock\recipe, last modified Sun Aug 27 22:50:21 2017
# ------------------------------------------------

package:
    name: r-aod
    version: '1.3'
source:
    fn: aod_1.3.tar.gz
    sha256: e377effe345987850ece985eabf79750ca1979d75469d17a323c21515ad1dda8
    url:
        - https://cran.r-project.org/src/contrib/aod_1.3.tar.gz
        - https://cran.r-project.org/src/contrib/Archive/aod/aod_1.3.tar.gz
build:
    noarch: ''
    noarch_python: false
    number: '0'
    rpaths:
        - lib/R/lib/
        - lib/
    string: r3.4.1_0
requirements:
    build:
        - m2w64-mpfr 3.1.4 4
        - msys2-conda-epoch 20160418 1
        - m2w64-libtiff 4.0.6 2
        - m2w64-libxml2 2.9.3 3
        - m2w64-xz 5.2.2 2
        - r-base 3.4.1 0
        - m2w64-bzip2 1.0.6 6
        - m2w64-tcl 8.6.5 3
        - m2w64-libiconv 1.14 6
        - m2w64-tk 8.6.5 3
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-flac 1.3.1 3
        - m2w64-bwidget 1.9.10 2
        - m2w64-zlib 1.2.8 10
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gsl 2.1 2
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-expat 2.1.1 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-wineditline 2.101 5
        - m2w64-speexdsp 1.2rc3 3
        - m2w64-libogg 1.3.2 3
        - m2w64-speex 1.2rc2 3
        - m2w64-libsndfile 1.0.26 2
        - m2w64-libvorbis 1.3.5 2
        - m2w64-fftw 3.3.4 6
        - m2w64-tktable 2.10 5
        - m2w64-gettext 0.19.7 2
        - m2w64-gmp 6.1.0 2
        - m2w64-libjpeg-turbo 1.4.2 3
        - m2w64-pcre 8.38 2
        - m2w64-libpng 1.6.21 2
    run:
        - r-base
test:
    commands:
        - '"%R%" -e "library(''aod'')"'
about:
    home: http://cran.r-project.org/package=aod
    license: GPL (>= 2)
    license_family: GPL3
    summary: This package provides a set of functions to analyse overdispersed counts
        or proportions. Most of the methods are already available elsewhere but are
        scattered in different packages. The proposed functions should be considered
        as complements to more sophisticated methods such as generalized estimating
        equations (GEE) or generalized linear mixed effect models (GLMM).
extra:
    final: true
    recipe-maintainers:
        - johanneskoester
        - bgruening
        - daler
