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harf
View on CRAN: Click
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Download and install harf package within the R console
Install from CRAN:
install.packages("harf")
Install from Github:
library("remotes")
install_github("cran/harf") Install by package version:
library("remotes")
install_version("harf", "0.1.0") Attach the package and use:
library("harf")
Maintained by
Cesaire J. K. Fouodo
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First Published: 2026-09-28
Latest Update: 2026-09-28
Description:
We extend Adversarial Random Forests to a high-dimensional framework. The method partitions the feature space into regions where the assumption of feature independence within tree leaves is more likely to hold. Region-specific adversarial random forest models are trained to capture local dependence structures, while an additional adversarial random forest is fitted to a meta-space representation to model dependencies between regions. New observations are generated by first sampling from the meta-space model and then conditionally sampling from each region-specific model. The proposed methodology is described in Fouodo et al. (2026) <doi:10.64898/2026.09.09.750490>.
How to cite:
Cesaire J. K. Fouodo (2026). harf: Adversarial Random Forests for Omics Synthesis. R package version 0.1.0, https://cran.r-project.org/web/packages/harf. Accessed 24 Oct. 2026.
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