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RFpredInterval  

Prediction Intervals with Random Forests and Boosted Forests
View on CRAN: Click here


Download and install RFpredInterval package within the R console
Install from CRAN:
install.packages("RFpredInterval")

Install from Github:
library("remotes")
install_github("cran/RFpredInterval")

Install by package version:
library("remotes")
install_version("RFpredInterval", "1.0.8")



Attach the package and use:
library("RFpredInterval")
Maintained by
Cansu Alakus
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-18
Latest Update:
Description:
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. (2022) and rfpi() builds 15 distinct variations of prediction intervals with random forests (RFPI) proposed by Roy and Larocque (2020) .
How to cite:
Cansu Alakus (2021). RFpredInterval: Prediction Intervals with Random Forests and Boosted Forests. R package version 1.0.8, https://cran.r-project.org/web/packages/RFpredInterval. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:18), 1.0.1 (2021-06-18 10:20), 1.0.2 (2021-06-28 22:40), 1.0.4 (2021-09-14 17:20), 1.0.5 (2022-01-20 20:42), 1.0.6 (2022-05-25 16:20), 1.0.7 (2023-03-06 08:50), 1.0.8 (2023-12-07 23:00)
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Complete documentation for RFpredInterval
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