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This algorithm is described in detail in the paper "Hedging Forecast Combinations With an Application to the Random Forest" by Beck et al. (2023) <doi:10.48550/arXiv.2308.15384>. The package provides a function hedgedrf() that can be used to train a Hedged Random Forest model on a dataset, and a function predict.hedgedrf() that can be used to make predictions with the model.
Version: | 0.0.1 |
Imports: | ranger, CVXR |
Published: | 2024-07-14 |
DOI: | 10.32614/CRAN.package.hedgedrf |
Author: | Elliot Beck [aut, cre] |
Maintainer: | Elliot Beck <elliot.beck at bf.uzh.ch> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | hedgedrf results |
Reference manual: | hedgedrf.pdf |
Package source: | hedgedrf_0.0.1.tar.gz |
Windows binaries: | r-devel: hedgedrf_0.0.1.zip, r-release: hedgedrf_0.0.1.zip, r-oldrel: hedgedrf_0.0.1.zip |
macOS binaries: | r-release (arm64): hedgedrf_0.0.1.tgz, r-oldrel (arm64): hedgedrf_0.0.1.tgz, r-release (x86_64): hedgedrf_0.0.1.tgz, r-oldrel (x86_64): hedgedrf_0.0.1.tgz |
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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.
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