# This file created by conda-build 3.20.4
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Thu Oct 22 18:43:31 2020
# ------------------------------------------------

package:
    name: r-timetk
    version: 2.5.0
source:
    sha256: b3ae015c72a8eb0a1c769aef558e7fb9ae7c918f4abd7c0ce93bc652390f98f1
    url:
        - https://cran.r-project.org/src/contrib/Archive/timetk/timetk_2.5.0.tar.gz
        - https://cran.r-project.org/src/contrib/timetk_2.5.0.tar.gz
build:
    merge_build_host: true
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r40h852d06f_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 2020.6.20 hecda079_0
        - 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-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 2020.1 216
        - 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 1.1.10 r40hda5aaf8_0
        - r-base 4.0.3 hc562dc2_2
        - r-base64enc 0.1_3 r40hda5aaf8_1004
        - r-callr 3.5.1 r40h142f84f_0
        - r-class 7.3_17 r40hda5aaf8_1
        - r-cli 2.1.0 r40h142f84f_0
        - r-clipr 0.7.1 r40h142f84f_0
        - r-codetools 0.2_17 r40h142f84f_0
        - r-colorspace 1.4_1 r40hda5aaf8_2
        - r-cpp11 0.2.3 r40h142f84f_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-digest 0.6.26 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 1.19.1 r40h6115d3f_0
        - r-generics 0.0.2 r40h6115d3f_1003
        - r-ggplot2 3.3.2 r40h6115d3f_0
        - 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_17 r40h20118fc_2
        - 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 r40h6115d3f_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 r40h796a38f_0
        - r-magrittr 1.5 r40h6115d3f_1003
        - 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 0.0.2 r40h6115d3f_0
        - r-munsell 0.5.0 r40h6115d3f_1003
        - r-nlme 3.1_149 r40h87ffe87_1
        - 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-pillar 1.4.6 r40h6115d3f_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 2.4.1 r40h6115d3f_1
        - r-rcolorbrewer 1.1_2 r40h6115d3f_1003
        - r-rcpp 1.0.5 r40h796a38f_0
        - r-rcpparmadillo 0.10.1.0.0 r40hc6cacc8_0
        - r-readr 1.4.0 r40h096a1c2_0
        - r-recipes 0.1.14 r40h142f84f_0
        - r-rlang 0.4.7 r40hda5aaf8_0
        - r-rpart 4.1_15 r40hda5aaf8_2
        - r-rprojroot 1.3_2 r40h6115d3f_1003
        - r-rsample 0.0.8 r40h6115d3f_0
        - r-rstudioapi 0.11 r40h6115d3f_1
        - 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 2.3.2 r40h796a38f_1
        - 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 0.3.4 r40hda5aaf8_0
        - r-viridislite 0.3.0 r40h6115d3f_1003
        - 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_1603392443008\_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
