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 |
| Reference manual: | MLFS.pdf |
| 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 |
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