# This file created by conda-build 3.20.5
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Sat Nov 21 15:51:41 2020
# ------------------------------------------------

package:
    name: r-timetk
    version: 2.6.0
source:
    sha256: 1d90c3ca2d6530cf3c651dc8f05a7b19df6e1e9f09ffa5f89555f9c3e1e82662
    url:
        - https://cran.r-project.org/src/contrib/Archive/timetk/timetk_2.6.0.tar.gz
        - https://cran.r-project.org/src/contrib/timetk_2.6.0.tar.gz
build:
    merge_build_host: true
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r40h6addd8b_0
requirements:
    build:
        - m2-gcc-libs 5.3.0 4
        - m2-libbz2 1.0.6 3
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-zip 3.0 2
        - msys2-conda-epoch 20160418 1
    host:
        - _r-mutex 1.0.1 anacondar_1
        - ca-certificates 2020.11.8 h5b45459_0
        - intel-openmp 2020.3 h57928b3_311
        - libblas 3.8.0 21_mkl
        - liblapack 3.8.0 21_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 heb44b8b_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 2020.4 hb70f87d_311
        - msys2-conda-epoch 20160418 1
        - openssl 1.1.1h he774522_0
        - r-anytime 0.3.9 r40h796a38f_0
        - r-askpass 1.1 r40hda5aaf8_2
        - r-assertthat 0.2.1 r40h6115d3f_2
        - r-backports 1.2.0 r40h6d2157b_0
        - r-base 4.0.3 hc562dc2_2
        - r-base64enc 0.1_3 r40hda5aaf8_1004
        - r-brio 1.1.0 r40h6d2157b_1
        - r-callr 3.5.1 r40h142f84f_0
        - r-class 7.3_17 r40hda5aaf8_1
        - r-cli 2.2.0 r40hc72bb7e_0
        - r-clipr 0.7.1 r40h142f84f_0
        - r-codetools 0.2_18 r40hc72bb7e_0
        - r-colorspace 2.0_0 r40h6d2157b_0
        - r-cpp11 0.2.4 r40hc72bb7e_0
        - r-crayon 1.3.4 r40h6115d3f_1003
        - r-crosstalk 1.1.0.1 r40h6115d3f_1
        - r-curl 4.3 r40hda5aaf8_1
        - r-data.table 1.13.2 r40h02096d4_0
        - r-desc 1.2.0 r40h6115d3f_1003
        - r-diffobj 0.3.2 r40h6d2157b_1
        - r-digest 0.6.27 r40h096a1c2_0
        - r-dplyr 1.0.2 r40h796a38f_0
        - r-ellipsis 0.3.1 r40hda5aaf8_0
        - r-evaluate 0.14 r40h6115d3f_2
        - r-fansi 0.4.1 r40hda5aaf8_1
        - r-farver 2.0.3 r40h796a38f_1
        - r-forcats 0.5.0 r40h6115d3f_1
        - r-forecast 8.13 r40haf2acee_0
        - r-fracdiff 1.5_1 r40h4dd0083_1
        - r-furrr 0.2.1 r40h142f84f_0
        - r-future 1.20.1 r40hc72bb7e_0
        - r-generics 0.1.0 r40hc72bb7e_0
        - r-ggplot2 3.3.2 r40hc72bb7e_1
        - r-globals 0.13.1 r40h142f84f_0
        - r-glue 1.4.2 r40hda5aaf8_0
        - r-gower 0.2.2 r40hda5aaf8_0
        - r-gtable 0.3.0 r40h6115d3f_3
        - r-hexbin 1.28.1 r40h87ffe87_2
        - r-hms 0.5.3 r40h6115d3f_1
        - r-htmltools 0.5.0 r40h796a38f_0
        - r-htmlwidgets 1.5.2 r40h142f84f_0
        - r-httr 1.4.2 r40h6115d3f_0
        - r-ipred 0.9_9 r40hda5aaf8_2
        - r-isoband 0.2.2 r40h796a38f_0
        - r-jsonlite 1.7.1 r40hda5aaf8_0
        - r-kernsmooth 2.23_18 r40h090b817_0
        - r-labeling 0.4.2 r40h142f84f_0
        - r-later 1.1.0.1 r40h796a38f_0
        - r-lattice 0.20_41 r40hda5aaf8_2
        - r-lava 1.6.8.1 r40hc72bb7e_0
        - r-lazyeval 0.2.2 r40hda5aaf8_2
        - r-lifecycle 0.2.0 r40h6115d3f_1
        - r-listenv 0.8.0 r40h6115d3f_1
        - r-lmtest 0.9_38 r40h87ffe87_1
        - r-lubridate 1.7.9.2 r40ha856d6a_0
        - r-magrittr 2.0.1 r40h6d2157b_1
        - r-mass 7.3_53 r40hda5aaf8_0
        - r-matrix 1.2_18 r40h0adb578_3
        - r-mgcv 1.8_33 r40h0adb578_0
        - r-mime 0.9 r40hda5aaf8_1
        - r-modeldata 0.1.0 r40h142f84f_0
        - r-munsell 0.5.0 r40h6115d3f_1003
        - r-nlme 3.1_150 r40h87ffe87_0
        - r-nnet 7.3_14 r40hda5aaf8_1
        - r-numderiv 2016.8_1.1 r40h6115d3f_3
        - r-openssl 1.4.3 r40h601d743_0
        - r-padr 0.5.3 r40h796a38f_0
        - r-parallelly 1.21.0 r40hc72bb7e_0
        - r-pillar 1.4.7 r40hc72bb7e_0
        - r-pkgbuild 1.1.0 r40h6115d3f_0
        - r-pkgconfig 2.0.3 r40h6115d3f_1
        - r-pkgload 1.1.0 r40h796a38f_0
        - r-plotly 4.9.2.1 r40h6115d3f_1
        - r-praise 1.0.0 r40h6115d3f_1004
        - r-prettyunits 1.1.1 r40h6115d3f_1
        - r-processx 3.4.4 r40hda5aaf8_0
        - r-prodlim 2019.11.13 r40h796a38f_1
        - r-promises 1.1.1 r40h796a38f_0
        - r-ps 1.4.0 r40h02096d4_0
        - r-purrr 0.3.4 r40hda5aaf8_1
        - r-quadprog 1.5_8 r40h20118fc_3
        - r-quantmod 0.4.17 r40h6115d3f_1
        - r-r6 2.5.0 r40hc72bb7e_0
        - r-rcolorbrewer 1.1_2 r40h6115d3f_1003
        - r-rcpp 1.0.5 r40ha856d6a_0
        - r-rcpparmadillo 0.10.1.2.0 r40h399f8d5_0
        - r-readr 1.4.0 r40h096a1c2_0
        - r-recipes 0.1.15 r40hc72bb7e_0
        - r-rematch2 2.1.2 r40h6115d3f_1
        - r-rlang 0.4.8 r40h6d2157b_0
        - r-rpart 4.1_15 r40hda5aaf8_2
        - r-rprojroot 2.0.2 r40hc72bb7e_0
        - r-rsample 0.0.8 r40h6115d3f_0
        - r-rstudioapi 0.13 r40hc72bb7e_0
        - r-scales 1.1.1 r40h6115d3f_0
        - r-slider 0.1.5 r40hda5aaf8_0
        - r-squarem 2020.5 r40h142f84f_0
        - r-stringi 1.5.3 r40h796a38f_0
        - r-stringr 1.4.0 r40h6115d3f_2
        - r-survival 3.2_7 r40hda5aaf8_0
        - r-sys 3.4 r40hda5aaf8_0
        - r-testthat 3.0.0 r40ha856d6a_0
        - r-tibble 3.0.4 r40h02096d4_0
        - r-tidyr 1.1.2 r40h796a38f_0
        - r-tidyselect 1.1.0 r40h6115d3f_0
        - r-timedate 3043.102 r40h6115d3f_1002
        - r-tseries 0.10_47 r40h20118fc_5
        - r-ttr 0.24.2 r40hda5aaf8_0
        - r-urca 1.3_0 r40h87ffe87_1006
        - r-utf8 1.1.4 r40hda5aaf8_1003
        - r-vctrs 0.3.5 r40h6d2157b_0
        - r-viridislite 0.3.0 r40h6115d3f_1003
        - r-waldo 0.2.3 r40hc72bb7e_0
        - r-warp 0.2.0 r40h02096d4_0
        - r-withr 2.3.0 r40h6115d3f_0
        - r-xts 0.12.1 r40hda5aaf8_0
        - r-yaml 2.2.1 r40hda5aaf8_1
        - r-zeallot 0.1.0 r40h6115d3f_1002
        - r-zoo 1.8_8 r40hda5aaf8_0
        - vc 14.1 h869be7e_1
        - vs2015_runtime 14.16.27012 h30e32a0_2
    run:
        - r-anytime
        - r-assertthat
        - r-base >=4.0,<4.1.0a0
        - r-dplyr >=0.7.0
        - r-forcats
        - r-forecast
        - r-ggplot2
        - r-hms
        - r-lazyeval >=0.2.0
        - r-lubridate >=1.6.0
        - r-padr >=0.3.0
        - r-plotly
        - r-purrr >=0.2.2
        - r-readr >=1.0.0
        - r-recipes >=0.1.4
        - r-rlang >=0.1.2
        - r-rsample
        - r-slider
        - r-stringi >=1.1.5
        - r-stringr
        - r-tibble >=1.2
        - r-tidyr >=0.6.1
        - r-timedate
        - r-xts >=0.9_7
        - r-zoo >=1.7_14
test:
    commands:
        - '"%R%" -e "library(''timetk'')"'
about:
    home: https://github.com/business-science/timetk
    license: GPL-3.0-or-later
    license_family: GPL3
    license_file:
        - D:\bld\r-timetk_1605974173760\_h_env/lib/R/share/licenses/GPL-3
    summary: 'Get the time series index (date or date-time component), time series
        signature (feature extraction of date or date-time component for time series
        machine learning), and time series summary (summary attributes about time
        series). Create future time series based on properties of existing time series
        index using logistic regression. Coerce between time-based tibbles (''tbl'')
        and ''xts'', ''zoo'', and ''ts''. Methods discussed herein are commonplace
        in machine learning, and have been cited in various literature. Refer to "Calendar
        Effects" in papers such as Taieb, Souhaib Ben. "Machine learning strategies
        for multi-step-ahead time series forecasting." Universit Libre de Bruxelles,
        Belgium (2014): 75-86. <http://souhaib-bentaieb.com/pdf/2014_phd.pdf>.'
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - benhuff
        - conda-forge/r
        - oblute
        - rluria14
