R Observatory: Metrics for quantregForest version 1.4-0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

quantregForest

1.4-0Package record

Quantile Regression Forests

4packages dependsuggested by 6

45.8Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Nicolai MeinshausenCRAN page ↗

Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled. The package is dependent on the package 'randomForest', written by Andy Liaw.

Changes in 1.4-0

New maintainer: Nicolai Meinshausen <meinshausen@gmail.com>.
Substantial speed improvements, all without changing results:
predict() now computes quantiles with a single vectorized sort per prediction matrix instead of calling quantile() once per observation (predictions on new data are now considerably faster; results are unchanged, type-7 quantiles as before).
Fitting with keep.inbag=TRUE previously used an O(n^2) loop per tree to sample out-of-bag responses; this is now fully vectorized. The overhead of keep.inbag=TRUE over a plain fit is reduced by more than an order of magnitude for larger n.
quantregForest() no longer computes the terminal-node matrix of the training data twice when keep.inbag=TRUE.

Show all changes in 1.4-0Hide the rest of the changes in 1.4-0

Out-of-bag predictions via predict() without newdata are much faster.
Removed a broken, unreachable duplicate definition of quantregForest() in R/convert.R that masked the real function during package collation.
quantregForest is now a pure R package. The bundled copy of the C/Fortran sources and R helper functions of the randomForest package (used only for fitting with nthreads > 1) has been removed; parallel fitting now calls randomForest() directly in each fork and merges the forests with randomForest::combine(). This removes the compiler dependency, keeps the parallel code path automatically in sync with upstream randomForest, and does not change the fitted forests.
RColorBrewer is no longer attached (it was needed only by the removed copies of randomForest plotting helpers).

From NEWS in the release

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("quantregForest", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-quantregforest

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-quantregForest

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-quantregForest

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 1.1 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.4-0

READMENoVignettesNoNEWSYes · 67% structured · mentions 1.4-0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 2
Examples that run: 100%2 run in a plain check
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 50%

How these are measured

Downloads

45.8K

CRAN downloads in the past year

Rank #2,100 · ~126/day · ~3.8K/mo

Releases R versions

Daily download trend is not available in this view yet.

2.7K30 days

8.4K90 days

45.8K1 year

Compare downloads with other packages →

Also on1.7K r2u10 autocran117 c2d4u

How downloads are counted

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Installing quantregForest adds 1 package (1 with compiled code, 80 KB of source tarballs). Heaviest: randomForest 80 KB.

Depends (1)

randomForest

Imports (2)

statsparallel

LinkingTo (0)

none

Suggests (3)

gss knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

4direct

0indirect

Imports 4

Suggested by 6

Depends, Imports or LinkingTo, most downloaded first

ConformalSmallest geomod curvir HCPclust

Suggests, most downloaded first

marginaleffects probably trtf vetiver ModelMap soilassessment

How these are counted

Code & Tests

People & History

People (2)

Nicolai Meinshausen

Author, Maintainer since 1.4-0 (2026)

Loris Michel

Author · added in 1.3-7.1

Previously maintained by Loris Michel (1.3-6 to 1.3-7.1) and Nicolai Meinshausen (0.1-0 to 1.3-5).

Listed in earlier versions (1)

Lukas Schiesser

no longer listed · 1.0 to 1.2

Releases (14)

Pick two releases to compare their code metrics.

1.4-0Latest
record
2026-07-03 · current release · diff ↗
R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
1.3-7.1
record
2024-10-07 · diff ↗
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23
1.3-7
record
2017-12-19 · diff ↗
1.3-6
record
2017-11-14 · diff ↗
R
R 3.4.0 released · 2017-04-21
1.3-5
record
2016-05-19 · diff ↗
R
R 3.3.0 released · 2016-05-03

Show 26 earlier eventsHide 26 earlier events

1.3
record
2016-04-29 · diff ↗ ·
removed 1 export
varImpPlot.qrf
1.2
record
2016-03-23 · diff ↗
1.1
record
2015-09-09 · diff ↗
1.0
record
2015-06-03 · diff ↗ ·
added 1 export
varImpPlot.qrf
R
R 3.2.0 released · 2015-04-16
R
R 3.1.0 released · 2014-04-10
R
R 3.0.0 released · 2013-04-03
0.2-3
record
2012-06-01 · diff ↗
R
R 2.15.0 released · 2012-03-30
R
R 2.14.0 released · 2011-10-31
R
R 2.13.0 released · 2011-04-13
R
R 2.12.0 released · 2010-10-15
R
R 2.11.0 released · 2010-04-22
R
R 2.10.0 released · 2009-10-26
R
R 2.9.0 released · 2009-04-17
R
R 2.8.0 released · 2008-10-20
R
R 2.7.0 released · 2008-04-22
R
R 2.6.0 released · 2007-10-03
R
R 2.5.0 released · 2007-04-24
0.2-2
record
2007-03-15 · diff ↗
0.2-1
record
2006-12-17 · diff ↗ ·
removed 1 export
predict.quantregForest
0.2-0
record
2006-12-15 · diff ↗
R
R 2.4.0 released · 2006-10-03
R
R 2.3.0 released · 2006-04-24
0.1-0
record
2006-02-08
R
R 2.2.0 released · 2005-10-06

Package metadata

First published: 2006-02-08
Total releases: 14 / 20 yrs
License: GPL
Download size: 6.9 KB

Appears in task views

Machine Learning & Statistical Learning

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("quantregForest")

Format

Meinshausen, N., & Michel, L. (2026). quantregForest: Quantile Regression Forests (Version 1.4-0) [Computer software]. https://doi.org/10.32614/CRAN.package.quantregForest

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for quantregForest version 1.4-0 [Data set]. HJJB, LLC. Data release v2026-10-17. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →