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 |