# This file created by conda-build 3.21.8
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Wed Apr 13 16:06:52 2022
# ------------------------------------------------

package:
  name: r-mcmcpack
  version: '1.6_3'
source:
  sha256: cb14ba20690b31fd813b05565484c866425f072a5ad99a5cbf1da63588958db3
  url:
    - https://cran.r-project.org/src/contrib/Archive/MCMCpack/MCMCpack_1.6-3.tar.gz
    - https://cran.r-project.org/src/contrib/MCMCpack_1.6-3.tar.gz
build:
  merge_build_host: true
  number: '0'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r40ha856d6a_0
requirements:
  build:
    - m2-autoconf 2.69 4
    - m2-automake-wrapper 10 2
    - m2-automake1.10 1.10.3 4
    - m2-automake1.11 1.11.6 4
    - m2-automake1.12 1.12.6 4
    - m2-automake1.13 1.13.4 5
    - m2-automake1.14 1.14.1 4
    - m2-automake1.15 1.15 3
    - m2-automake1.6 1.6.3 3
    - m2-automake1.7 1.7.9 3
    - m2-automake1.8 1.8.5 4
    - m2-automake1.9 1.9.6 3
    - m2-bash 4.3.042 5
    - m2-coreutils 8.25 102
    - m2-db 5.3.28 3
    - m2-diffutils 3.3 4
    - m2-filesystem 2016.04 4
    - m2-gawk 4.1.3 2
    - m2-gcc-libs 5.3.0 4
    - m2-gdbm 1.11 4
    - m2-gettext 0.19.7 4
    - m2-glib2 2.48.0 2
    - m2-gmp 6.1.0 3
    - m2-grep 2.22 4
    - m2-libasprintf 0.19.7 4
    - m2-libbz2 1.0.6 3
    - m2-libcrypt 1.3 2
    - m2-libdb 5.3.28 3
    - m2-libffi 3.2.1 2
    - m2-libgcrypt 1.6.4 2
    - m2-libgdbm 1.11 4
    - m2-libgettextpo 0.19.7 4
    - m2-libgpg-error 1.21 2
    - m2-libiconv 1.14 3
    - m2-libintl 0.19.7 4
    - m2-liblzma 5.2.2 2
    - m2-libpcre 8.38 2
    - m2-libreadline 6.3.008 8
    - m2-libxml2 2.9.2 3
    - m2-libxslt 1.1.28 8
    - m2-m4 1.4.17 5
    - m2-make 4.1 5
    - m2-mpfr 3.1.4 2
    - m2-msys2-runtime 2.5.0.17080.65c939c 3
    - m2-ncurses 6.0.20160220 2
    - m2-perl 5.22.1 2
    - m2-pkg-config 0.29.1 2
    - m2-sed 4.2.2 3
    - m2-zip 3.0 2
    - m2-zlib 1.2.8 4
    - 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 2022.0.0 h57928b3_3663
    - libblas 3.9.0 14_win64_mkl
    - liblapack 3.9.0 14_win64_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-icu 58.2 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 3
    - 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 2022.0.0 h0e2418a_796
    - msys2-conda-epoch 20160418 1
    - r-backports 1.4.1 r40h6d2157b_0
    - r-base 4.0.5 hddad469_6
    - r-brio 1.1.3 r40h6d2157b_0
    - r-callr 3.7.0 r40hc72bb7e_0
    - r-caret 6.0_91 r40h6d2157b_0
    - r-class 7.3_20 r40h6d2157b_0
    - r-cli 3.2.0 r40ha856d6a_0
    - r-coda 0.19_4 r40hc72bb7e_0
    - r-codetools 0.2_18 r40hc72bb7e_0
    - r-colorspace 2.0_3 r40h6d2157b_0
    - r-conquer 1.3.0 r40h01f9f87_0
    - r-cpp11 0.4.2 r40hc72bb7e_0
    - r-crayon 1.5.1 r40hc72bb7e_0
    - r-data.table 1.14.2 r40h6d2157b_0
    - r-desc 1.4.1 r40hc72bb7e_0
    - r-diffobj 0.3.5 r40h6d2157b_0
    - r-digest 0.6.29 r40ha856d6a_0
    - r-dplyr 1.0.8 r40ha856d6a_0
    - r-e1071 1.7_9 r40ha856d6a_0
    - r-ellipsis 0.3.2 r40h6d2157b_0
    - r-evaluate 0.15 r40hc72bb7e_0
    - r-fansi 1.0.3 r40h6d2157b_0
    - r-farver 2.1.0 r40ha856d6a_0
    - r-foreach 1.5.2 r40hc72bb7e_0
    - r-future 1.24.0 r40hc72bb7e_0
    - r-future.apply 1.8.1 r40hc72bb7e_0
    - r-generics 0.1.2 r40hc72bb7e_0
    - r-ggplot2 3.3.5 r40hc72bb7e_0
    - r-globals 0.14.0 r40hc72bb7e_0
    - r-glue 1.6.2 r40h6d2157b_0
    - r-gower 1.0.0 r40h6d2157b_0
    - r-gtable 0.3.0 r40hc72bb7e_3
    - r-hardhat 0.2.0 r40hc72bb7e_0
    - r-ipred 0.9_12 r40h6d2157b_0
    - r-isoband 0.2.5 r40ha856d6a_0
    - r-iterators 1.0.14 r40hc72bb7e_0
    - r-jsonlite 1.8.0 r40h6d2157b_0
    - r-kernsmooth 2.23_20 r40h090b817_0
    - r-labeling 0.4.2 r40hc72bb7e_1
    - r-lattice 0.20_45 r40h6d2157b_0
    - r-lava 1.6.10 r40hc72bb7e_0
    - r-lifecycle 1.0.1 r40hc72bb7e_0
    - r-listenv 0.8.0 r40hc72bb7e_1
    - r-lubridate 1.8.0 r40ha856d6a_0
    - r-magrittr 2.0.3 r40h6d2157b_0
    - r-mass 7.3_56 r40h6d2157b_0
    - r-matrix 1.4_1 r40hd2e18ed_0
    - r-matrixmodels 0.5_0 r40hc72bb7e_0
    - r-matrixstats 0.61.0 r40h6d2157b_0
    - r-mcmc 0.9_7 r40h6d2157b_2
    - r-mgcv 1.8_40 r40hd2e18ed_0
    - r-modelmetrics 1.2.2.2 r40ha856d6a_1
    - r-munsell 0.5.0 r40hc72bb7e_1004
    - r-nlme 3.1_157 r40he816bda_0
    - r-nnet 7.3_17 r40h6d2157b_0
    - r-numderiv 2016.8_1.1 r40hc72bb7e_3
    - r-parallelly 1.31.0 r40hc72bb7e_0
    - r-pillar 1.7.0 r40hc72bb7e_0
    - r-pkgconfig 2.0.3 r40hc72bb7e_1
    - r-pkgload 1.2.4 r40ha856d6a_0
    - r-plyr 1.8.7 r40ha856d6a_0
    - r-praise 1.0.0 r40hc72bb7e_1005
    - r-proc 1.18.0 r40ha856d6a_0
    - r-processx 3.5.3 r40h6d2157b_0
    - r-prodlim 2019.11.13 r40ha856d6a_1
    - r-progressr 0.10.0 r40hc72bb7e_0
    - r-proxy 0.4_26 r40h6d2157b_0
    - r-ps 1.6.0 r40h6d2157b_0
    - r-purrr 0.3.4 r40h6d2157b_1
    - r-quantreg 5.88 r40hb106f1f_0
    - r-r6 2.5.1 r40hc72bb7e_0
    - r-rcolorbrewer 1.1_3 r40h785f33e_0
    - r-rcpp 1.0.8.3 r40ha856d6a_0
    - r-rcpparmadillo 0.11.0.0.0 r40h399f8d5_0
    - r-recipes 0.2.0 r40hc72bb7e_0
    - r-rematch2 2.1.2 r40hc72bb7e_1
    - r-reshape2 1.4.4 r40ha856d6a_1
    - r-rlang 1.0.2 r40ha856d6a_0
    - r-rpart 4.1.16 r40h6d2157b_0
    - r-rprojroot 2.0.3 r40hc72bb7e_0
    - r-rstudioapi 0.13 r40hc72bb7e_0
    - r-scales 1.1.1 r40hc72bb7e_0
    - r-sparsem 1.81 r40he816bda_0
    - r-squarem 2021.1 r40hc72bb7e_0
    - r-stringi 1.7.6 r40ha856d6a_2
    - r-stringr 1.4.0 r40hc72bb7e_2
    - r-survival 3.3_1 r40h6d2157b_0
    - r-testthat 3.1.3 r40ha856d6a_0
    - r-tibble 3.1.6 r40h6d2157b_0
    - r-tidyr 1.2.0 r40ha856d6a_0
    - r-tidyselect 1.1.2 r40h6addd8b_0
    - r-timedate 3043.102 r40hc72bb7e_1002
    - r-utf8 1.2.2 r40h6d2157b_0
    - r-vctrs 0.4.0 r40ha856d6a_0
    - r-viridislite 0.4.0 r40hc72bb7e_0
    - r-waldo 0.4.0 r40hc72bb7e_0
    - r-withr 2.5.0 r40hc72bb7e_0
    - tbb 2021.5.0 h2d74725_1
    - ucrt 10.0.20348.0 h57928b3_0
    - vc 14.2 hb210afc_6
    - vs2015_runtime 14.29.30037 h902a5da_6
  run:
    - m2w64-gcc-libs
    - r-base >=4.0,<4.1.0a0
    - r-coda >=0.11_3
    - r-lattice
    - r-mass
    - r-mcmc
    - r-quantreg
test:
  commands:
    - '"%R%" -e "library(''MCMCpack'')"'
about:
  home: https://CRAN.R-project.org/package=MCMCpack
  license: GPL-3.0-only
  license_family: GPL3
  license_file:
    - D:\bld\r-mcmcpack_1649866278974\_h_env/lib/R/share/licenses/GPL-3
  summary: Contains functions to perform Bayesian inference using posterior simulation
    for a number of statistical models. Most simulation is done in compiled C++ written
    in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc
    objects that can then be summarized using the 'coda' package. Some useful utility
    functions such as density functions, pseudo-random number generators for statistical
    distributions, a general purpose Metropolis sampling algorithm, and tools for
    visualization are provided.
extra:
  copy_test_source_files: true
  final: true
  recipe-maintainers:
    - conda-forge/r
