Package: rfinterval 1.0.0

rfinterval: Predictive Inference for Random Forests

An integrated package for constructing random forest prediction intervals using a fast implementation package 'ranger'. This package can apply the following three methods described in Haozhe Zhang, Joshua Zimmerman, Dan Nettleton, and Daniel J. Nordman (2019) <doi:10.1080/00031305.2019.1585288>: the out-of-bag prediction interval, the split conformal method, and the quantile regression forest.

Authors:Haozhe Zhang [aut, cre]

rfinterval_1.0.0.tar.gz
rfinterval_1.0.0.zip(r-4.7)rfinterval_1.0.0.zip(r-4.6)rfinterval_1.0.0.zip(r-4.5)
rfinterval_1.0.0.tgz(r-4.6-any)rfinterval_1.0.0.tgz(r-4.5-any)
rfinterval_1.0.0.tar.gz(r-4.7-any)rfinterval_1.0.0.tar.gz(r-4.6-any)
rfinterval_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rfinterval/json (API)

# Install 'rfinterval' in R:

install.packages('rfinterval', repos = c('https://haozhestat.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/haozhestat/rfinterval/issues

Datasets:

BeijingPM25 - Beijing PM2.5 Air Pollution Data

On CRAN:

4.30 score 13 stars 31 scripts 199 downloads 2 exports 6 dependencies

Last updated from:3d007d8e60. Checks:7 ERROR, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	ERROR	109
source / vignettes	OK	161
linux-release-x86_64	ERROR	114
macos-release-arm64	ERROR	127
macos-oldrel-arm64	ERROR	115
windows-devel	ERROR	73
windows-release	ERROR	64
windows-oldrel	ERROR	74
wasm-release	OK	98