caretForecast: Conformal Time Series Forecasting Using State of Art Machine
Learning Algorithms
Conformal time series forecasting using the caret infrastructure.
It provides access to state-of-the-art machine learning models for forecasting
applications. The hyperparameter of each model is selected based on time
series cross-validation, and forecasting is done recursively.
| Version: |
0.1.2 |
| Depends: |
R (≥ 3.6) |
| Imports: |
forecast (≥ 8.15), caret (≥ 6.0.88), magrittr (≥ 2.0.1), methods (≥ 4.1.1), dplyr (≥ 1.0.9), generics (≥ 0.1.3) |
| Suggests: |
Cubist (≥ 0.3.0), knitr (≥ 1.29), testthat (≥ 2.3.2) |
| Published: |
2026-01-30 |
| DOI: |
10.32614/CRAN.package.caretForecast |
| Author: |
Resul Akay [aut, cre] |
| Maintainer: |
Resul Akay <resulakay1 at gmail.com> |
| BugReports: |
https://github.com/Akai01/caretForecast/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://akai01.github.io/caretForecast/,
https://github.com/Akai01/caretForecast |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
caretForecast results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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