# This file created by conda-build 2.1.18
# meta.yaml template originally from:
# C:\projects\r-corpcor-feedstock\recipe, last modified Thu Apr 05 09:51:23 2018
# ------------------------------------------------

package:
    name: r-corpcor
    version: 1.6.9
source:
    fn: corpcor_1.6.9.tar.gz
    sha256: 2e4fabd1d3936fecea67fa365233590147ca50bb45cf80efb53a10345a8a23c2
    url:
        - https://cran.r-project.org/src/contrib/corpcor_1.6.9.tar.gz
        - https://cran.r-project.org/src/contrib/Archive/corpcor/corpcor_1.6.9.tar.gz
build:
    noarch: ''
    noarch_python: false
    number: '0'
    rpaths:
        - lib/R/lib/
        - lib/
    string: r3.3.2_0
requirements:
    build:
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-libcrypt 1.3 2
        - m2-libexpat 2.1.1 2
        - m2-gcc-libs 5.3.0 4
        - m2-heimdal-libs 1.5.3 10
        - m2-libidn 1.32 2
        - m2-info 6.0 2
        - m2w64-make 4.1.2351.a80a8b8 2
        - m2w64-libxml2 2.9.3 4
        - m2-bash 4.3.042 5
        - m2-ncurses 6.0.20160220 2
        - m2-libintl 0.19.7 4
        - m2w64-speexdsp 1.2rc3 3
        - m2-icu 56.1 2
        - m2w64-tktable 2.10 5
        - m2w64-headers-git 5.0.0.4636.c0ad18a 2
        - m2-gmp 6.1.0 3
        - m2w64-fftw 3.3.4 6
        - m2w64-gettext 0.19.7 2
        - m2w64-gcc-objc 5.3.0 6
        - m2w64-mpfr 3.1.4 4
        - m2-gzip 1.7 2
        - m2-findutils 4.6.0 2
        - m2-libdb 5.3.28 3
        - m2w64-gcc-ada 5.3.0 6
        - m2-libgdbm 1.11 4
        - m2-texinfo 6.0 2
        - m2-curl 7.47.1 3
        - m2w64-binutils 2.25.1 5
        - r-base 3.3.2 5
        - m2-libpcre 8.38 2
        - m2-libtasn1 4.7 2
        - m2-libp11-kit 0.23.2 2
        - m2-p11-kit 0.23.2 2
        - m2w64-toolchain 5.3.0 7
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2-db 5.3.28 3
        - 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-openssl 1.0.2.g 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
        - m2w64-crt-git 5.0.0.4636.2595836 2
        - m2-texinfo-tex 6.0 2
        - m2-perl 5.22.1 2
        - m2-libmetalink 0.1.2 3
        - m2w64-libtiff 4.0.6 2
        - m2w64-windows-default-manifest 6.4 3
        - m2w64-bzip2 1.0.6 6
        - m2w64-tcl 8.6.5 3
        - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
        - m2w64-tk 8.6.5 3
        - m2-libffi 3.2.1 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
        - m2-p7zip 9.38.1 2
        - m2w64-gsl 2.1 2
        - m2w64-winpthreads-git 5.0.0.4634.697f757 2
        - m2-libcurl 7.47.1 3
        - m2-libopenssl 1.0.2.g 2
        - m2-ca-certificates 20150426 103
        - m2-zlib 1.2.8 4
        - m2-sed 4.2.2 3
        - m2w64-tools-git 5.0.0.4592.90b8472 2
        - m2w64-flac 1.3.1 3
        - m2w64-libvorbis 1.3.5 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-gdbm 1.11 4
        - m2w64-libiconv 1.14 6
        - m2w64-gcc-libs-core 5.3.0 7
        - m2-libsqlite 3.10.0.0 2
        - m2-libssh2 1.6.0 2
        - m2w64-gcc 5.3.0 6
        - m2w64-expat 2.1.1 2
        - m2-libedit 3.1 20150326
        - m2w64-speex 1.2rc2 3
        - m2w64-gmp 6.1.0 2
        - m2w64-libsndfile 1.0.26 2
    run:
        - r-base
test:
    commands:
        - '"%R%" -e "library(''corpcor'')"'
about:
    home: http://strimmerlab.org/software/corpcor/
    license: GPL (>= 3)
    license_family: GPL3
    license_file: C:\bld\r-corpcor_1522922052259\_b_env\R\share\licenses\GPL-3
    summary: Implements a James-Stein-type shrinkage estimator for  the covariance
        matrix, with separate shrinkage for variances and correlations.   The details
        of the method are explained in Schafer and Strimmer (2005) <doi:10.2202/1544-6115.1175>
        and Opgen-Rhein and Strimmer (2007) <doi:10.2202/1544-6115.1252>. The approach
        is both computationally as well as statistically very efficient, it is applicable
        to "small n, large p" data, and always returns a positive definite and well-conditioned
        covariance matrix. In addition to inferring the covariance matrix the package
        also provides shrinkage estimators for partial correlations and partial variances.
        The inverse of the covariance and correlation matrix can be efficiently computed,
        as well as any arbitrary power of the shrinkage correlation matrix. Furthermore,
        functions are available for fast singular value decomposition, for computing
        the pseudoinverse, and for checking the rank and positive definiteness of
        a matrix.
extra:
    final: true
    recipe-maintainers:
        - johanneskoester
        - bgruening
        - daler
        - jdblischak
        - cbrueffer
