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hedgedrf: An Implementation of the Hedged Random Forest Algorithm

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 ORCID iD [aut, cre]
Maintainer: Elliot Beck <elliot.beck at bf.uzh.ch>
License: GPL-3
NeedsCompilation: no
CRAN checks: hedgedrf results

Documentation:

Reference manual: hedgedrf.pdf

Downloads:

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

Linking:

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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.