MLFS: Machine Learning Forest Simulator

Climate-sensitive forest simulator based on the principles of machine learning. It stimulates all key processes in the forest: radial growth, height growth, mortality, crown recession, regeneration and harvesting. The method for predicting tree heights was described by Skudnik and Jevšenak (2022) <doi:10.1016/j.foreco.2022.120017>, while the method for predicting basal area increments (BAI) was described by Jevšenak and Skudnik (2021) <doi:10.1016/j.foreco.2020.118601>.

Version: 0.4.2
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: 2022-04-20
Author: Jernej Jevsenak
Maintainer: Jernej Jevsenak <jernej.jevsenak at gmail.com>
License: GPL-3
NeedsCompilation: no
Citation: MLFS citation info
Materials: NEWS
CRAN checks: MLFS results

Documentation:

Reference manual: MLFS.pdf

Downloads:

Package source: MLFS_0.4.2.tar.gz
Windows binaries: r-devel: MLFS_0.4.2.zip, r-release: MLFS_0.4.2.zip, r-oldrel: MLFS_0.4.2.zip
macOS binaries: r-release (arm64): MLFS_0.4.2.tgz, r-oldrel (arm64): MLFS_0.4.2.tgz, r-release (x86_64): MLFS_0.4.2.tgz

Linking:

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