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 |
| 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:
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