R Observatory: Metrics for mboost version 2.9-14

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

mboost

2.9-14Package record

Model-Based Boosting

22packages dependsuggested by 16

83.9Kdownloads / year

73.3%test coverage

8/13flavors OK

Overview

About

Maintained by Torsten HothornCRAN page ↗GitHub ↗Issues ↗

Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. Models and algorithms are described in doi:10.1214/07-STS242, a hands-on tutorial is available from doi:10.1007/s00180-012-0382-5. The package allows user-specified loss functions and base-learners.

Changes in 2.9-14

Other

Unify warnings.

From inst/NEWS.Rd in the release

Install

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

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

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

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("boost-R/mboost")

Development version from boost-R/mboost. Installs pak first if it is not already available.

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-mboost

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-mboost

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-mboost

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

5NOTE8OK

Check messages

NOTEtestsr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64

r-devel-linux-x86_64-debian-clang

Running ‘birds_Biometrics.R’ [14s/18s]
  Comparing ‘birds_Biometrics.Rout’ to ‘birds_Biometrics.Rout.save’ ... OK
  Running ‘bugfixes.R’ [70s/83s]
  Comparing ‘bugfixes.Rout’ to ‘bugfixes.Rout.save’ ...
891c891,907
< There were 14 warnings (use warnings() to see them)
---
> Warning messages:
> 1: In bols(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 2: In bbs(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 3: In bols(z1, df = 4, contrasts.arg = "contr.dummy") :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 4: In bbs(x1, x2, df = 6) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may
...[truncated]...
 bols(X, df = ncol(X)) :
---
> Warning message:
> In bols(X, df = ncol(X)) :
300d292
< 2: object length is not a multiple of subscript length 
  Running ‘regtest-blackboost.R’ [76s/98s]
  Comparing ‘regtest-blackboost.Rout’ to ‘regtest-blackboost.Rout.save’ ... OK
  Running ‘regtest-family.R’ [21s/25s]
  Comparing ‘regtest-family.Rout’ to ‘regtest-family.Rout.save’ ... OK
  Running ‘regtest-gamboost.R’ [10s/13s]
  Comparing ‘regtest-gamboost.Rout’ to ‘regtest-gamboost.Rout.save’ ...
757,758d756
< Warning message:
< object length is not a multiple of subscript length 
763,764d760
< Warning message:
< object length is not a multiple of subscript length 
  Running ‘regtest-glmboost.R’ [12s/15s]
  Comparing ‘regtest-glmboost.Rout’ to ‘regtest-glmboost.Rout.save’ ... OK
  Running ‘regtest-hatmatrix.R’ [2s/3s]
  Comparing ‘regtest-hatmatrix.Rout’ to ‘regtest-hatmatrix.Rout.save’ ... OK
  Running ‘regtest-varimp.R’ [4s/4s]
  Comparing ‘regtest-varimp.Rout’ to ‘regtest-varimp.Rout.save’ ... OK

r-devel-linux-x86_64-debian-gcc

Running ‘birds_Biometrics.R’ [11s/12s]
  Comparing ‘birds_Biometrics.Rout’ to ‘birds_Biometrics.Rout.save’ ... OK
  Running ‘bugfixes.R’ [41s/46s]
  Comparing ‘bugfixes.Rout’ to ‘bugfixes.Rout.save’ ...
891c891,907
< There were 14 warnings (use warnings() to see them)
---
> Warning messages:
> 1: In bols(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 2: In bbs(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 3: In bols(z1, df = 4, contrasts.arg = "contr.dummy") :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 4: In bbs(x1, x2, df = 6) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may
...[truncated]...
 In bols(X, df = ncol(X)) :
---
> Warning message:
> In bols(X, df = ncol(X)) :
300d292
< 2: object length is not a multiple of subscript length 
  Running ‘regtest-blackboost.R’ [43s/48s]
  Comparing ‘regtest-blackboost.Rout’ to ‘regtest-blackboost.Rout.save’ ... OK
  Running ‘regtest-family.R’ [13s/16s]
  Comparing ‘regtest-family.Rout’ to ‘regtest-family.Rout.save’ ... OK
  Running ‘regtest-gamboost.R’ [6s/7s]
  Comparing ‘regtest-gamboost.Rout’ to ‘regtest-gamboost.Rout.save’ ...
757,758d756
< Warning message:
< object length is not a multiple of subscript length 
763,764d760
< Warning message:
< object length is not a multiple of subscript length 
  Running ‘regtest-glmboost.R’ [9s/10s]
  Comparing ‘regtest-glmboost.Rout’ to ‘regtest-glmboost.Rout.save’ ... OK
  Running ‘regtest-hatmatrix.R’ [2s/2s]
  Comparing ‘regtest-hatmatrix.Rout’ to ‘regtest-hatmatrix.Rout.save’ ... OK
  Running ‘regtest-varimp.R’ [3s/3s]
  Comparing ‘regtest-varimp.Rout’ to ‘regtest-varimp.Rout.save’ ... OK

r-devel-linux-x86_64-fedora-clang

Running ‘birds_Biometrics.R’ [10s/10s]
  Comparing ‘birds_Biometrics.Rout’ to ‘birds_Biometrics.Rout.save’ ... OK
  Running ‘bugfixes.R’ [45s/47s]
  Comparing ‘bugfixes.Rout’ to ‘bugfixes.Rout.save’ ...
891c891,907
< There were 14 warnings (use warnings() to see them)
---
> Warning messages:
> 1: In bols(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 2: In bbs(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 3: In bols(z1, df = 4, contrasts.arg = "contr.dummy") :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 4: In bbs(x1, x2, df = 6) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may
...[truncated]...
c290,291
< Warning messages:
< 1: In bols(X, df = ncol(X)) :
---
> Warning message:
> In bols(X, df = ncol(X)) :
300d292
< 2: object length is not a multiple of subscript length 
  Running ‘regtest-blackboost.R’ [51s/53s]
  Comparing ‘regtest-blackboost.Rout’ to ‘regtest-blackboost.Rout.save’ ... OK
  Running ‘regtest-family.R’ [12s/13s]
  Comparing ‘regtest-family.Rout’ to ‘regtest-family.Rout.save’ ... OK
  Running ‘regtest-gamboost.R’
  Comparing ‘regtest-gamboost.Rout’ to ‘regtest-gamboost.Rout.save’ ...
757,758d756
< Warning message:
< object length is not a multiple of subscript length 
763,764d760
< Warning message:
< object length is not a multiple of subscript length 
  Running ‘regtest-glmboost.R’
  Comparing ‘regtest-glmboost.Rout’ to ‘regtest-glmboost.Rout.save’ ... OK
  Running ‘regtest-hatmatrix.R’
  Comparing ‘regtest-hatmatrix.Rout’ to ‘regtest-hatmatrix.Rout.save’ ... OK
  Running ‘regtest-varimp.R’
  Comparing ‘regtest-varimp.Rout’ to ‘regtest-varimp.Rout.save’ ... OK

r-devel-linux-x86_64-fedora-gcc

Running ‘birds_Biometrics.R’ [10s/11s]
  Comparing ‘birds_Biometrics.Rout’ to ‘birds_Biometrics.Rout.save’ ... OK
  Running ‘bugfixes.R’ [46s/49s]
  Comparing ‘bugfixes.Rout’ to ‘bugfixes.Rout.save’ ...
891c891,907
< There were 14 warnings (use warnings() to see them)
---
> Warning messages:
> 1: In bols(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 2: In bbs(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 3: In bols(z1, df = 4, contrasts.arg = "contr.dummy") :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 4: In bbs(x1, x2, df = 6) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may
...[truncated]...
c290,291
< Warning messages:
< 1: In bols(X, df = ncol(X)) :
---
> Warning message:
> In bols(X, df = ncol(X)) :
300d292
< 2: object length is not a multiple of subscript length 
  Running ‘regtest-blackboost.R’ [51s/53s]
  Comparing ‘regtest-blackboost.Rout’ to ‘regtest-blackboost.Rout.save’ ... OK
  Running ‘regtest-family.R’ [12s/13s]
  Comparing ‘regtest-family.Rout’ to ‘regtest-family.Rout.save’ ... OK
  Running ‘regtest-gamboost.R’
  Comparing ‘regtest-gamboost.Rout’ to ‘regtest-gamboost.Rout.save’ ...
757,758d756
< Warning message:
< object length is not a multiple of subscript length 
763,764d760
< Warning message:
< object length is not a multiple of subscript length 
  Running ‘regtest-glmboost.R’
  Comparing ‘regtest-glmboost.Rout’ to ‘regtest-glmboost.Rout.save’ ... OK
  Running ‘regtest-hatmatrix.R’
  Comparing ‘regtest-hatmatrix.Rout’ to ‘regtest-hatmatrix.Rout.save’ ... OK
  Running ‘regtest-varimp.R’
  Comparing ‘regtest-varimp.Rout’ to ‘regtest-varimp.Rout.save’ ... OK

r-devel-windows-x86_64

Running 'birds_Biometrics.R' [15s]
  Comparing 'birds_Biometrics.Rout' to 'birds_Biometrics.Rout.save' ... OK
  Running 'bugfixes.R' [62s]
  Comparing 'bugfixes.Rout' to 'bugfixes.Rout.save' ...
891c891,907
< There were 14 warnings (use warnings() to see them)
---
> Warning messages:
> 1: In bols(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 2: In bbs(x1) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 3: In bols(z1, df = 4, contrasts.arg = "contr.dummy") :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend on different numbers of observations.
> 4: In bbs(x1, x2, df = 6) :
>   base-learner contains missing values; missing values are excluded per base-learner, i.e., base-learners may depend 
...[truncated]...
rning messages:
< 1: In bols(X, df = ncol(X)) :
---
> Warning message:
> In bols(X, df = ncol(X)) :
300d292
< 2: object length is not a multiple of subscript length 
  Running 'regtest-blackboost.R' [55s]
  Comparing 'regtest-blackboost.Rout' to 'regtest-blackboost.Rout.save' ... OK
  Running 'regtest-family.R' [18s]
  Comparing 'regtest-family.Rout' to 'regtest-family.Rout.save' ... OK
  Running 'regtest-gamboost.R' [7s]
  Comparing 'regtest-gamboost.Rout' to 'regtest-gamboost.Rout.save' ...
757,758d756
< Warning message:
< object length is not a multiple of subscript length 
763,764d760
< Warning message:
< object length is not a multiple of subscript length 
  Running 'regtest-glmboost.R' [12s]
  Comparing 'regtest-glmboost.Rout' to 'regtest-glmboost.Rout.save' ... OK
  Running 'regtest-hatmatrix.R' [2s]
  Comparing 'regtest-hatmatrix.Rout' to 'regtest-hatmatrix.Rout.save' ... OK
  Running 'regtest-varimp.R' [3s]
  Comparing 'regtest-varimp.Rout' to 'regtest-varimp.Rout.save' ... OK

CRAN check page ↗

Slowest check: 10.0 min · r-oldrel-macos-x86_64

Status changes

NOTE8 OK, 5 NOTENow
NOTE12 OK, 1 NOTE2026-09-13
OK13 OK2026-09-10
NOTE12 OK, 1 NOTE2026-07-30
OK13 OK2026-07-24
ERROR12 OK, 1 ERROR2026-07-23

Show 4 earlier changesHide 4 earlier changes

OK13 OK2026-07-18
ERROR8 OK, 4 NOTE, 1 ERROR2026-07-16
NOTE11 OK, 2 NOTE2026-07-10
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 2.9-14

README· In the repository, left out of the releaseVignettesYes · 4 · dynamicNEWSYes · mentions 2.9-14Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION

Help pages: 19 (1 internal)includes a package overview page
Examples that run: 94%15 run in a plain check · 1 never run
Exported functions with examples: 82%
Documented parameters: 72%
Return-value docs: 88%
Help pages citing references: 63% with a bibliography file

Also includes 3 demo scripts (run with demo())

Vignettes (4)

How these are measured

Downloads

83.9K

CRAN downloads in the past year

Rank #1,455 · ~230/day · ~7K/mo

Releases R versions

Daily download trend is not available in this view yet.

6.2K30 days

17.8K90 days

83.9K1 year

Compare downloads with other packages →

Also on1.1K r2u8 autocran9K conda_forge1.1K c2d4u

How downloads are counted

Repository

boost-r/mboost ↗Organization: boost-R

77Stars

28Forks

30Open issues

2Open PRs

0Releases

1,330Commits

20Commit identities

mboostcranboosting-algorithmstutorialsmachine-learningr-languagevariable-selectionmodelling

1,330 commits · Last activity 2026-09-22

Responsiveness

How these are sampled

PRs merged (all time): 75%
Median days to close, 50 most recently updated closed issues: 1
Median days to close, 50 most recently updated closed PRs: 1

Forks over time

2026-07-14 · 272026-07-24 · 28

How these are measured

PracticesBeta

2 development-tooling and community-health practices detected across 1 family in the upstream repository

Checks run against github.com/boost-r/mboost on 2026-10-18.

Continuous integration (2)

Travis CI (config file)AppVeyor

How this is detected·Detection ruleset v3 (2026-09-26)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Claude Codefirst seen 2026-07-23
Commits: 2 by its own account · at least 2 crediting it in the message
GitHub Copilotfirst seen 2026-07-23
Pull request: opened by its own account
Commits: 3 by its own account

From outside contributors

Claude Code
Pull requests: 1 from outside contributors, first on 2026-07-23, 1 from forks

Models named in its commits

Claude Fable 52 commits · Jul 2026

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

15 external dependencies (excludes base and recommended)

Installing mboost adds 11 packages (7 with compiled code, 6.9 MB of source tarballs). Heaviest: partykit 2.1 MB, sandwich 1.4 MB, mvtnorm 1.0 MB.

Depends (5)

R >= 3.2.0methodsstatsparallelstabs

Imports (10)

Matrixsurvivalsplineslatticennls quadprogutilsgraphicsgrDevicespartykit

LinkingTo (0)

none

Suggests (15)

TH.dataMASSfields BayesX gbm mlbench RColorBrewerrpartrandomForestnnetkangar00 bibtex lme4nlmecobs

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

22direct

2indirect

Depends 9 · Imports 13

Suggested by 16

Show all 38 packagesHide all 38 packages

Depends, Imports or LinkingTo, most downloaded first

censored gamboostLSS FDboost carSurv mgwrsar tbm GeDS expectreg survML biospear bujar InvariantCausalPrediction DIFboost geoGAM MacroFilters survalis boostrq gfboost RobustPrediction sgboost mermboost spboost

Suggests, most downloaded first

HSAUR3 mlr stabs HSAUR2 catdata pre mlr3fda tidypredict MachineShop peperr spikeSlabGAM survex SuperSurv imputeR civic.icarm NRMstatsML

How these are counted

Code & Tests

People & History

People (8)

Torsten Hothorn

Maintainer since 2.9-4 (2020), Author

Peter Buehlmann

Author · added in 2.0-0

Benjamin Hofner

Author · added in 2.6.0

Thomas Kneib

Author · added in 2.6.0

Matthias Schmid

Author · added in 2.6.0

Andreas Mayr

Contributor · added in 2.8-0

Fabian Otto-Sobotka

Contributor · added in 2.9-4

Fabian Scheipl

Contributor · added in 2.1-2

Previously maintained by Benjamin Hofner (2.6-0 to 2.9-3) and Torsten Hothorn (0.4-6 to 2.5-0).

Listed in earlier versions (2)

Peter Buhlmann

no longer listed · 0.4-6 to 2.10.1

Fabian Sobotka

no longer listed · 2.1-2 to 2.9-3

Releases (99)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
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
R
R 3.4.0 released · 2017-04-21
R
R 3.3.0 released · 2016-05-03
R
R 3.2.0 released · 2015-04-16
R
R 3.1.0 released · 2014-04-10
3.0.2Latest
record
2013-09-09 · current release · diff ↗
R
R 3.0.0 released · 2013-04-03
2.15.3
record
2013-02-08 · diff ↗

Show 110 earlier eventsHide 110 earlier events

2.15.2
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2012-09-27 · diff ↗
R
R 2.15.0 released · 2012-03-30
2.14.2
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2012-02-29 · diff ↗
2.14.1
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2011-11-28 · diff ↗
R
R 2.14.0 released · 2011-10-31
2.13.2
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2011-08-22 · diff ↗
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R 2.13.0 released · 2011-04-13
2.13.0
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2011-03-17 · diff ↗
2.12.2
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2.12.1
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2010-11-19 · diff ↗
R
R 2.12.0 released · 2010-10-15
2.12.0
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2.11.1
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2010-05-22 · diff ↗
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R 2.11.0 released · 2010-04-22
2.11.0
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2.10.1
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2009-11-18 · diff ↗
R
R 2.10.0 released · 2009-10-26
2.10.0
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2009-09-21 · diff ↗
2.9-14
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2026-09-06 · diff ↗ ·
removed 2 exports
bss, bns
2.9-13
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2026-07-17 · diff ↗
2.9-12
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2026-07-15 · diff ↗
2.9-11
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2024-08-22 · diff ↗
2.9-10
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2024-04-29 · diff ↗
2.9-9
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2023-12-07 · diff ↗
2.9-8
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2023-09-06 · diff ↗
2.9-7
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2022-04-26 · diff ↗
2.9-6
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2.9-5
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2021-04-14 · diff ↗
2.9-4
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2020-12-10 · diff ↗
2.9-3
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2020-08-06 · diff ↗
2.9-2.1
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2020-08-02 · diff ↗
2.9-2
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2020-02-18 · diff ↗
2.9-1
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2018-08-22 · diff ↗
2.9-0
record
2018-06-14 · diff ↗ ·
added 4 exports
RCG, predict.mboost, predict.glmboost, downstream.test
R
R 2.9.0 released · 2009-04-17
2.9.0
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2009-03-27 · diff ↗ ·
added 1 export
QuantReg
2.8-1
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2017-07-23 · diff ↗
2.8.1
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2008-12-02 · diff ↗
2.8-0
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2017-05-04 · diff ↗ ·
added 2 exports
bkernel, fitted.mboost
2.7-0
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2016-11-23 · diff ↗ ·
added 11 exports
Cindex, plot.glmboost, plot.mboost, lines.mboost, plot.cvrisk, plot.mboost.ci, lines.mboost.ci, print.glmboost.ci, varimp, plot.varimp, as.data.frame.varimp
2.6-0
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2016-03-12 · diff ↗ ·
removed 3 exports
df2lambda, hyper_bbs, bl_lin

added 1 export
mboost_intern
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
2.6.0
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2007-07-08 · diff ↗ ·
removed 1 export
AIC.gb

added 8 exports
bbs, bss, bns, bols, bspatial, brandom, btree, survFit
2.5.1
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2007-05-31 · diff ↗
2.5-0
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2015-08-14 · diff ↗
R
R 2.5.0 released · 2007-04-24
2.5.0
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2007-04-18 · diff ↗
2.4-2
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2015-02-12 · diff ↗ ·
added 3 exports
df2lambda, hyper_bbs, bl_lin
2.4-1
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2014-12-16 · diff ↗ ·
added 1 export
selected.mboost
2.4.1
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2006-12-06 · diff ↗
2.4-0
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2014-10-02 · diff ↗ ·
removed 2 exports
stabsel, stabsel_parameters

added 4 exports
stabsel.mboost, stabsel_parameters.mboost, confint.mboost, confint.glmboost
R
R 2.4.0 released · 2006-10-03
2.4.0
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2006-09-14 · diff ↗
2.3-0
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2006-06-16
R
R 2.3.0 released · 2006-04-24

Package metadata

First published: 2006-06-16
Total releases: 99 / 20 yrs
License: GPL-2 OSI
Minimum R: ≥ 3.2.0
Download size: 2.0 MB

Appears in task views

Machine Learning & Statistical Learning Survival Analysis

Cite

Cite this package

Run in R for the authors' entry:

citation("mboost")

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Cite the R Observatory

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Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mboost version 2.9-14 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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