# This file created by conda-build 2.1.17
# meta.yaml template originally from:
# C:\projects\r-brglm-feedstock\recipe, last modified Mon Aug 14 13:39:09 2017
# ------------------------------------------------

package:
    name: r-brglm
    version: '0.5_9'
source:
    fn: brglm_0.5-9.tar.gz
    sha256: 5b70bc8216d1af37304e5e7c6e902b92327cc2aad5798ea6ba1634dfab921d92
    url:
        - https://cran.r-project.org/src/contrib/brglm_0.5-9.tar.gz
        - https://cran.r-project.org/src/contrib/Archive/brglm/brglm_0.5-9.tar.gz
build:
    noarch: ''
    noarch_python: false
    number: '0'
    rpaths:
        - lib/R/lib/
        - lib/
    string: r3.4.1_0
requirements:
    build:
        - m2-tzcode 2015.e 2
        - m2w64-crt-git 5.0.0.4636.2595836 2
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2w64-libxml2 2.9.3 3
        - m2-libcrypt 1.3 2
        - r-base 3.4.1 0
        - m2-which 2.21 3
        - m2-mintty 1!2.2.3 2
        - m2-catgets 1.1 3
        - m2-gcc-libs 5.3.0 4
        - m2-libbz2 1.0.6 3
        - m2-sed 4.2.2 3
        - m2-libxml2 2.9.2 3
        - m2-info 6.0 2
        - m2w64-make 4.1.2351.a80a8b8 2
        - m2-bash 4.3.042 5
        - m2-libintl 0.19.7 4
        - m2w64-speexdsp 1.2rc3 3
        - m2w64-tktable 2.10 5
        - m2w64-headers-git 5.0.0.4636.c0ad18a 2
        - m2-gmp 6.1.0 3
        - m2-time 1.7 2
        - m2w64-fftw 3.3.4 6
        - m2w64-gettext 0.19.7 2
        - m2w64-gcc-objc 5.3.0 6
        - m2-bash-completion 2.3 2
        - m2w64-mpfr 3.1.4 4
        - m2-libutil-linux 2.26.2 2
        - m2-make 4.1 5
        - m2-gzip 1.7 2
        - m2-findutils 4.6.0 2
        - m2w64-gcc-ada 5.3.0 6
        - m2-util-linux 2.26.2 2
        - m2-unzip 6.0 3
        - m2-zip 3.0 2
        - m2-base 1.0.0 2
        - m2-libgettextpo 0.19.7 4
        - m2w64-binutils 2.25.1 5
        - m2-libpcre 8.38 2
        - m2w64-toolchain 5.3.0 7
        - r-profilemodel 0.5_9 0a
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2-inetutils 1.9.2 2
        - m2-coreutils 8.25 102
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-wineditline 2.101 5
        - m2w64-libogg 1.3.2 3
        - m2w64-mpc 1.0.3 3
        - m2-libiconv 1.14 3
        - m2-tftp-hpa 5.2 2
        - m2w64-libjpeg-turbo 1.4.2 3
        - m2w64-pcre 8.38 2
        - m2w64-libpng 1.6.21 2
        - m2w64-isl 0.16.1 2
        - m2-gettext 0.19.7 4
        - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
        - m2w64-libtiff 4.0.6 2
        - m2-tar 1.28 4
        - m2w64-windows-default-manifest 6.4 3
        - m2w64-bzip2 1.0.6 6
        - m2w64-tcl 8.6.5 3
        - m2-gawk 4.1.3 2
        - m2-liblzma 5.2.2 2
        - m2w64-tk 8.6.5 3
        - m2w64-flac 1.3.1 3
        - m2-ttyrec 1.0.8 2
        - m2-less 481 2
        - m2w64-pkg-config 0.29.1 2
        - 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-winpthreads-git 5.0.0.4634.697f757 2
        - m2-zlib 1.2.8 4
        - m2-libcatgets 1.1 3
        - m2-filesystem 2016.04 4
        - m2w64-tools-git 5.0.0.4592.90b8472 2
        - m2w64-libvorbis 1.3.5 2
        - r 3.1.3 0
        - posix 1.0.0 2
        - m2-libreadline 6.3.008 8
        - msys2-conda-epoch 20160418 1
        - m2w64-gcc-fortran 5.3.0 6
        - m2w64-xz 5.2.2 2
        - m2-ncurses 6.0.20160220 2
        - m2-msys2-launcher-git 0.3.28.860c495 2
        - m2w64-libiconv 1.14 6
        - m2-dash 0.5.8 2
        - m2w64-gcc-libs-core 5.3.0 7
        - m2-libasprintf 0.19.7 4
        - m2-file 5.25 2
        - m2-diffutils 3.3 4
        - m2w64-gcc 5.3.0 6
        - m2-grep 2.22 4
        - m2w64-expat 2.1.1 2
        - m2-mpfr 3.1.4 2
        - m2w64-speex 1.2rc2 3
        - m2w64-gmp 6.1.0 2
        - m2w64-libsndfile 1.0.26 2
    run:
        - r-base
        - r-profilemodel
test:
    commands:
        - '"%R%" -e "library(''brglm'')"'
about:
    home: http://www.ucl.ac.uk/~ucakiko/index.html
    license: GPL (>= 2)
    license_family: GPL3
    summary: Fit generalized linear models with binomial responses using either an
        adjusted-score approach to bias reduction or maximum penalized likelihood
        where penalization is by Jeffreys invariant prior. These procedures return
        estimates with improved frequentist properties (bias, mean squared error)
        that are always finite even in cases where the maximum likelihood estimates
        are infinite (data separation). Fitting takes place by fitting generalized
        linear models on iteratively updated pseudo-data. The interface is essentially
        the same as 'glm'.  More flexibility is provided by the fact that custom pseudo-data
        representations can be specified and used for model fitting. Functions are
        provided for the construction of confidence intervals for the reduced-bias
        estimates.
extra:
    final: true
    recipe-maintainers:
        - johanneskoester
        - bgruening
