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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
DOI: 10.32614/CRAN.package.MLFS
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, r-oldrel (x86_64): MLFS_0.4.2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=MLFS to link to this page.

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.
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