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-any)rfinterval_1.0.0.zip(r-4.6-any)rfinterval_1.0.0.zip(r-4.5-any)
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✨
DESCRIPTION
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:

On CRAN:

Conda:

4.28 score 12 stars 32 scripts 256 downloads 2 exports 6 dependencies

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

TargetResultTimeFilesSyslog
linux-develERROR142
source / vignettesOK146
linux-releaseERROR97
macos-releaseERROR128
macos-oldrelERROR121
windows-develERROR68
windows-releaseERROR67
windows-oldrelERROR72
wasm-releaseOK89

Exports:rfintervalsim_data

Dependencies:latticeMASSMatrixrangerRcppRcppEigen