# This file created by conda-build 3.20.4
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Tue Oct 20 17:29:20 2020
# ------------------------------------------------

package:
    name: r-dppackage
    version: 1.1_7.4
source:
    sha256: a6a9a8d1a85873a4dbe5894d376f811630731122e6a2d4266e2173b96629dc51
    url:
        - https://cran.r-project.org/src/contrib/Archive/DPpackage/DPpackage_1.1-7.4.tar.gz
        - https://cran.r-project.org/src/contrib/DPpackage_1.1-7.4.tar.gz
build:
    merge_build_host: true
    number: '1004'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r40h87ffe87_1004
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-pcre2 10.34 0
        - 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 4.0.3 hc562dc2_2
        - r-lattice 0.20_41 r40hda5aaf8_2
        - r-mass 7.3_53 r40hda5aaf8_0
        - r-matrix 1.2_18 r40h0adb578_3
        - r-nlme 3.1_149 r40h87ffe87_1
        - r-survival 3.2_7 r40hda5aaf8_0
    run:
        - m2w64-gcc-libs
        - r-base >=4.0,<4.1.0a0
        - r-mass
        - r-nlme
        - r-survival
test:
    commands:
        - '"%R%" -e "library(''DPpackage'')"'
about:
    home: http://www.mat.puc.cl/~ajara
    license: GPL-2.0-or-later
    license_family: GPL3
    license_file:
        - D:\bld\r-dppackage_1603215236852\_h_env/lib/R/share/licenses/GPL-2
    summary: Functions to perform inference via simulation from the posterior distributions
        for Bayesian nonparametric and semiparametric models. Although the name of
        the package was motivated by the Dirichlet Process prior, the package considers
        and will consider other priors on functional spaces. So far, DPpackage includes
        models considering Dirichlet Processes, Dependent Dirichlet Processes, Dependent
        Poisson- Dirichlet Processes, Hierarchical Dirichlet Processes, Polya Trees,
        Linear Dependent Tailfree Processes, Mixtures of Triangular distributions,
        Random Bernstein polynomials priors and Dependent Bernstein Polynomials.  The
        package also includes models considering Penalized B-Splines.  Includes semiparametric
        models for marginal and conditional density estimation, ROC curve analysis,
        interval censored data, binary regression models, generalized linear mixed
        models, IRT type models, and generalized additive models. Also contains functions
        to compute Pseudo-Bayes factors for model comparison, and to elicitate the
        precision parameter of the Dirichlet Process. To maximize computational efficiency,
        the actual sampling for each model is done in compiled FORTRAN. The functions
        return objects which can be subsequently analyzed with functions provided
        in the 'coda' package.
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - conda-forge/r
