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-4.5)rfinterval_1.0.0.zip(r-4.4)rfinterval_1.0.0.zip(r-4.3)
rfinterval_1.0.0.tgz(r-4.4-any)rfinterval_1.0.0.tgz(r-4.3-any)
rfinterval_1.0.0.tar.gz(r-4.5-noble)rfinterval_1.0.0.tar.gz(r-4.4-noble)
rfinterval_1.0.0.tgz(r-4.4-emscripten)rfinterval_1.0.0.tgz(r-4.3-emscripten)
rfinterval.pdf |rfinterval.html✨
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:

4.23 score 13 stars 26 scripts 108 downloads 2 exports 6 dependencies

Last updated 5 years agofrom:3d007d8e60. Checks:OK: 1 ERROR: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 31 2024
R-4.5-win	ERROR	Oct 31 2024
R-4.5-linux	ERROR	Oct 31 2024
R-4.4-win	ERROR	Oct 31 2024
R-4.4-mac	ERROR	Oct 31 2024
R-4.3-win	ERROR	Oct 31 2024
R-4.3-mac	ERROR	Oct 31 2024