A 'modeltime' extension that implements time series ensemble forecasting methods including model averaging,
weighted averaging, and stacking. These techniques are popular methods
to improve forecast accuracy and stability.
| Version: |
1.0.4 |
| Depends: |
modeltime (≥ 1.2.3), modeltime.resample (≥ 0.2.1), R (≥
3.5) |
| Imports: |
tune (≥ 0.1.2), rsample, yardstick, workflows (≥ 0.2.1), recipes (≥ 0.1.15), timetk (≥ 2.5.0), tibble, dplyr (≥
1.0.0), tidyr, purrr, stringr, rlang (≥ 0.1.2), cli, generics, magrittr, tictoc, parallel, doParallel, foreach, glmnet |
| Suggests: |
gt, dials, utils, earth, testthat, tidymodels, xgboost, lubridate, knitr, rmarkdown |
| Published: |
2024-07-19 |
| DOI: |
10.32614/CRAN.package.modeltime.ensemble |
| Author: |
Matt Dancho [aut, cre],
Business Science [cph] |
| Maintainer: |
Matt Dancho <mdancho at business-science.io> |
| BugReports: |
https://github.com/business-science/modeltime.ensemble/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://business-science.github.io/modeltime.ensemble/,
https://github.com/business-science/modeltime.ensemble |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
modeltime.ensemble results |