# This file created by conda-build 3.20.4
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Tue Oct 20 21:53:14 2020
# ------------------------------------------------

package:
    name: r-vgam
    version: '1.1_3'
source:
    sha256: 0c9ff51b9ee76d8b182a19b61f278970ad6d421c0206bfef40b7413b7acb94c3
    url:
        - https://cran.r-project.org/src/contrib/Archive/VGAM/VGAM_1.1-3.tar.gz
        - https://cran.r-project.org/src/contrib/VGAM_1.1-3.tar.gz
build:
    merge_build_host: true
    number: '2'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r36h87ffe87_2
requirements:
    build:
        - m2-bash 4.3.042 5
        - m2-coreutils 8.25 102
        - m2-filesystem 2016.04 4
        - m2-gcc-libs 5.3.0 4
        - m2-gmp 6.1.0 3
        - m2-libbz2 1.0.6 3
        - m2-libiconv 1.14 3
        - m2-libintl 0.19.7 4
        - m2-make 4.1 5
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-sed 4.2.2 3
        - m2-zip 3.0 2
        - m2w64-binutils 2.25.1 5
        - m2w64-bzip2 1.0.6 6
        - m2w64-crt-git 5.0.0.4636.2595836 2
        - m2w64-gcc 5.3.0 6
        - m2w64-gcc-ada 5.3.0 6
        - m2w64-gcc-fortran 5.3.0 6
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gcc-objc 5.3.0 6
        - m2w64-gmp 6.1.0 2
        - m2w64-headers-git 5.0.0.4636.c0ad18a 2
        - m2w64-isl 0.16.1 2
        - m2w64-libiconv 1.14 6
        - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-make 4.1.2351.a80a8b8 2
        - m2w64-mpc 1.0.3 3
        - m2w64-mpfr 3.1.4 4
        - m2w64-pkg-config 0.29.1 2
        - m2w64-toolchain 5.3.0 7
        - m2w64-toolchain_win-64 2.4.0 0
        - m2w64-tools-git 5.0.0.4592.90b8472 2
        - m2w64-windows-default-manifest 6.4 3
        - m2w64-winpthreads-git 5.0.0.4634.697f757 2
        - m2w64-zlib 1.2.8 10
        - msys2-conda-epoch 20160418 1
    host:
        - _r-mutex 1.0.1 anacondar_1
        - intel-openmp 2020.1 216
        - libblas 3.8.0 16_mkl
        - liblapack 3.8.0 16_mkl
        - m2w64-bwidget 1.9.10 2
        - m2w64-bzip2 1.0.6 6
        - m2w64-expat 2.1.1 2
        - m2w64-fftw 3.3.4 6
        - m2w64-flac 1.3.1 3
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gettext 0.19.7 2
        - m2w64-gmp 6.1.0 2
        - m2w64-gsl 2.1 2
        - m2w64-libiconv 1.14 6
        - m2w64-libjpeg-turbo 1.4.2 3
        - m2w64-libogg 1.3.2 3
        - m2w64-libpng 1.6.21 2
        - m2w64-libsndfile 1.0.26 2
        - m2w64-libtiff 4.0.6 2
        - m2w64-libvorbis 1.3.5 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-libxml2 2.9.3 4
        - m2w64-mpfr 3.1.4 4
        - m2w64-pcre 8.38 2
        - m2w64-speex 1.2rc2 3
        - m2w64-speexdsp 1.2rc3 3
        - m2w64-tcl 8.6.5 3
        - m2w64-tk 8.6.5 3
        - m2w64-tktable 2.10 5
        - m2w64-wineditline 2.101 5
        - m2w64-xz 5.2.2 2
        - m2w64-zlib 1.2.8 10
        - mkl 2020.1 216
        - msys2-conda-epoch 20160418 1
        - r-base 3.6.3 hc562dc2_4
    run:
        - m2w64-gcc-libs
        - r-base >=3.6,<3.7.0a0
test:
    commands:
        - '"%R%" -e "library(''VGAM'')"'
about:
    home: https://www.stat.auckland.ac.nz/~yee/VGAM
    license: GPL-3.0-only
    license_family: GPL3
    license_file: D:\bld\r-vgam_1603231023057\_h_env/lib/R/share/licenses/GPL-3
    summary: 'An implementation of about 6 major classes of statistical regression
        models. The central algorithm is Fisher scoring and iterative reweighted least
        squares. At the heart of this package are the vector generalized linear and
        additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate
        GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized
        Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7>
        gives details of the statistical framework and the package. Currently only
        fixed-effects models are implemented. Many (150+) models and distributions
        are estimated by maximum likelihood estimation (MLE) or penalized MLE. The
        other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank
        VGAMs, RCIMs (row-column interaction models)---these classes perform constrained
        and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well
        as constrained additive ordination (CAO). Note that these functions are subject
        to change; see the NEWS and ChangeLog files for latest changes.'
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - conda-forge/r
        - croth1
