MLFS: Machine Learning Forest Simulator

Climate-sensitive, single-tree forest simulator based on data-driven machine learning. It simulates the main forest processes— radial growth, height growth, mortality, crown recession, regeneration, and harvesting—so users can assess stand development under climate and management scenarios. The height model is described by Skudnik and Jevšenak (2022) <doi:10.1016/j.foreco.2022.120017>, the basal-area increment model by Jevšenak and Skudnik (2021) <doi:10.1016/j.foreco.2020.118601>, and an overview of the MLFS package, workflow, and applications is provided by Jevšenak, Arnič, Krajnc, and Skudnik (2023), Ecological Informatics <doi:10.1016/j.ecoinf.2023.102115>.

Version:	0.4.3
Depends:	R (≥ 3.4)
Imports:	brnn (≥ 0.6), ranger (≥ 0.13.1), reshape2 (≥ 1.4.4), pscl (≥ 1.5.5), naivebayes (≥ 0.9.7), magrittr (≥ 1.5), dplyr (≥ 0.7.0), tidyr (≥ 1.1.3), tidyselect (≥ 1.0.0)
Published:	2025-09-01
DOI:	10.32614/CRAN.package.MLFS
Author:	Jernej Jevsenak [aut, cre, cph]
Maintainer:	Jernej Jevsenak <jernej.jevsenak at gmail.com>
BugReports:	https://github.com/jernejjevsenak/MLFS/issues
License:	GPL-3
URL:	https://CRAN.R-project.org/package=MLFS
NeedsCompilation:	no
Citation:	MLFS citation info
Materials:	NEWS
CRAN checks:	MLFS results

Documentation:

Reference manual:

MLFS.html , MLFS.pdf

Downloads:

Package source:	MLFS_0.4.3.tar.gz
Windows binaries:	r-devel: MLFS_0.4.3.zip, r-release: MLFS_0.4.3.zip, r-oldrel: MLFS_0.4.3.zip
macOS binaries:	r-release (arm64): MLFS_0.4.3.tgz, r-oldrel (arm64): MLFS_0.4.3.tgz, r-release (x86_64): MLFS_0.4.3.tgz, r-oldrel (x86_64): MLFS_0.4.3.tgz
Old sources:	MLFS archive

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