RFpredInterval: Prediction Intervals with Random Forests and Boosted Forests

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: 1.0.4
Depends: R (≥ 3.6.0)
Imports: ranger, data.table, hdrcde, parallel, data.tree, DiagrammeR
Suggests: knitr, rmarkdown, testthat
Published: 2021-09-14
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

Documentation:

Reference manual: RFpredInterval.pdf

Downloads:

Package source: RFpredInterval_1.0.4.tar.gz
Windows binaries: r-devel: RFpredInterval_1.0.4.zip, r-devel-UCRT: RFpredInterval_1.0.4.zip, r-release: RFpredInterval_1.0.4.zip, r-oldrel: RFpredInterval_1.0.4.zip
macOS binaries: r-release (arm64): RFpredInterval_1.0.4.tgz, r-release (x86_64): RFpredInterval_1.0.4.tgz, r-oldrel: RFpredInterval_1.0.4.tgz
Old sources: RFpredInterval archive

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