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'))

Peer review:

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

Datasets:

On CRAN:

2 exports 13 stars 1.64 score 6 dependencies 22 scripts 165 downloads

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

TargetResultDate
Doc / VignettesOKAug 21 2024
R-4.5-winERRORAug 21 2024
R-4.5-linuxERRORJul 22 2024
R-4.4-winERRORAug 21 2024
R-4.4-macERRORAug 21 2024
R-4.3-winERRORAug 21 2024
R-4.3-macERRORAug 21 2024

Exports:rfintervalsim_data

Dependencies:latticeMASSMatrixrangerRcppRcppEigen