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Fits non-linear regression models on dependant data with Generalised Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta (2020) <doi:10.48550/arXiv.2007.15421>.
| Version: | 0.1.4 |
| Depends: | R (≥ 3.3.0) |
| Imports: | BRISC, parallel, stats, matrixStats, randomForest, pbapply |
| Suggests: | knitr, rmarkdown, ggplot2, testthat (≥ 2.1.0) |
| Published: | 2022-04-28 |
| Author: | Arkajyoti Saha [aut, cre], Sumanta Basu [aut], Abhirup Datta [aut] |
| Maintainer: | Arkajyoti Saha <arkajyotisaha93 at gmail.com> |
| BugReports: | https://github.com/ArkajyotiSaha/RandomForestsGLS/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/ArkajyotiSaha/RandomForestsGLS |
| NeedsCompilation: | yes |
| CRAN checks: | RandomForestsGLS results |
| Reference manual: | RandomForestsGLS.pdf |
| Vignettes: |
How to use RandomForestsGLS |
| Package source: | RandomForestsGLS_0.1.4.tar.gz |
| Windows binaries: | r-devel: RandomForestsGLS_0.1.4.zip, r-release: RandomForestsGLS_0.1.4.zip, r-oldrel: RandomForestsGLS_0.1.4.zip |
| macOS binaries: | r-release (arm64): RandomForestsGLS_0.1.4.tgz, r-oldrel (arm64): RandomForestsGLS_0.1.4.tgz, r-release (x86_64): RandomForestsGLS_0.1.4.tgz, r-oldrel (x86_64): RandomForestsGLS_0.1.4.tgz |
| Old sources: | RandomForestsGLS archive |
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