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: 0.1.1
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: 2022-10-24
DOI: 10.32614/CRAN.package.caretForecast
Author: Resul Akay [aut, cre]
Maintainer: Resul Akay <resulakay1 at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: caretForecast results


Reference manual: caretForecast.pdf


Package source: caretForecast_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): caretForecast_0.1.1.tgz, r-oldrel (arm64): caretForecast_0.1.1.tgz, r-release (x86_64): caretForecast_0.1.1.tgz, r-oldrel (x86_64): caretForecast_0.1.1.tgz
Old sources: caretForecast archive

Reverse dependencies:

Reverse imports: OptiSembleForecasting, WaveletETS, WaveletGBM, WaveletKNN, WaveletLSTM


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