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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 |
| Reference manual: | modeltime.ensemble.pdf |
| Vignettes: |
Getting Started with Modeltime Ensemble Iterative Forecasting with Nested Ensembles Autoregressive Forecasting (Recursive Ensembles) |
| Package source: | modeltime.ensemble_1.0.4.tar.gz |
| Windows binaries: | r-devel: modeltime.ensemble_1.0.4.zip, r-release: modeltime.ensemble_1.0.4.zip, r-oldrel: modeltime.ensemble_1.0.4.zip |
| macOS binaries: | r-release (arm64): modeltime.ensemble_1.0.4.tgz, r-oldrel (arm64): modeltime.ensemble_1.0.4.tgz, r-release (x86_64): modeltime.ensemble_1.0.4.tgz, r-oldrel (x86_64): modeltime.ensemble_1.0.4.tgz |
| Old sources: | modeltime.ensemble archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.