modeltime.gluonts: 'GluonTS' Deep Learning

Use the 'GluonTS' deep learning library inside of 'modeltime'. Available models include 'DeepAR', 'N-BEATS', and 'N-BEATS' Ensemble. Refer to "GluonTS - Probabilistic Time Series Modeling" (<https://ts.gluon.ai/index.html>).

Version: 0.1.0
Depends: modeltime (≥ 0.3.1)
Imports: parsnip, timetk, magrittr, rlang (≥ 0.1.2), reticulate, tibble, forcats, dplyr, tidyr, purrr, stringr, glue, fs
Suggests: tidyverse, tidymodels, knitr, rmarkdown, roxygen2, testthat
Published: 2020-11-30
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho at business-science.io>
BugReports: https://github.com/business-science/modeltime.gluonts/issues
License: MIT + file LICENSE
URL: https://github.com/business-science/modeltime.gluonts
NeedsCompilation: no
Materials: README NEWS
CRAN checks: modeltime.gluonts results

Downloads:

Reference manual: modeltime.gluonts.pdf
Vignettes: Getting Started with Modeltime GluonTS
Package source: modeltime.gluonts_0.1.0.tar.gz
Windows binaries: r-devel: modeltime.gluonts_0.1.0.zip, r-release: modeltime.gluonts_0.1.0.zip, r-oldrel: modeltime.gluonts_0.1.0.zip
macOS binaries: r-release (arm64): modeltime.gluonts_0.1.0.tgz, r-release (x86_64): modeltime.gluonts_0.1.0.tgz, r-oldrel: modeltime.gluonts_0.1.0.tgz

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