Implements various prediction interval methods with random forests and boosted forests. The package has two main functions: pibf() produces prediction intervals with boosted forests (PIBF) as described in Alakus et al. (2021) <arXiv:2106.08217> and rfpi() builds 15 distinct variations of prediction intervals with random forests (RFPI) proposed by Roy and Larocque (2020) <doi:10.1177/0962280219829885>.
Version: | 1.0.2 |
Depends: | R (≥ 3.6.0) |
Imports: | ranger, data.table, hdrcde, parallel, data.tree, DiagrammeR |
Suggests: | knitr, rmarkdown, testthat |
Published: | 2021-06-28 |
Author: | Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb] (Author of included randomForestSRC codes), Udaya B. Kogalur [ctb] (Author of included randomForestSRC codes) |
Maintainer: | Cansu Alakus <cansu.alakus at hec.ca> |
BugReports: | https://github.com/calakus/RFpredInterval/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/calakus/RFpredInterval |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | RFpredInterval results |
Reference manual: | RFpredInterval.pdf |
Package source: | RFpredInterval_1.0.2.tar.gz |
Windows binaries: | r-devel: RFpredInterval_1.0.2.zip, r-devel-UCRT: RFpredInterval_1.0.2.zip, r-release: RFpredInterval_1.0.1.zip, r-oldrel: RFpredInterval_1.0.1.zip |
macOS binaries: | r-release (arm64): RFpredInterval_1.0.1.tgz, r-release (x86_64): RFpredInterval_1.0.2.tgz, r-oldrel: RFpredInterval_1.0.2.tgz |
Old sources: | RFpredInterval archive |
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