mbest

0.6.1

Moment-Based Estimation for Hierarchical Models

1packages depend

29.4Kdownloads / year

76.4%test coverage

9/13checks pass

Overview

About

Maintained by Ben BolkerFirst published 2014-06-056 releasesCRAN page ↗GitHub ↗

Fast moment-based hierarchical model fitting. Implements methods from the papers "Fast Moment-Based Estimation for Hierarchical Models," by Perry (2017) and "Fitting a Deeply Nested Hierarchical Model to a Large Book Review Dataset Using a Moment-Based Estimator," by Zhang, Schmaus, and Perry (2018).

Install

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

install.packages("mbest", 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("patperry/r-mbest")

Development version from patperry/r-mbest. 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-mbest

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

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-mbest

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-mbest

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

4NOTE9OK

Failing flavors

NOTE r-devel-linux-x86_64-debian-clang
NOTE r-devel-linux-x86_64-debian-gcc
NOTE r-devel-linux-x86_64-fedora-gcc
NOTE r-devel-windows-x86_64

Slowest check: 4.4 min · r-devel-linux-x86_64-fedora-clang

Code health

Yes

Tests · ratio 0.24

76.4%

Coverage · measured lines

100%

Documentation · exports

Dependencies · direct

Check history

NOTE2026-07-16
11 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 57%
Return-value docs: 50%
References docs: 38%

Downloads

29.4K

CRAN downloads in the past year

Rank #2,544 · ~81/day · ~2.5K/mo

Releases R versions

Daily download trend is not available in this view yet.

1.4K30 days

8.6K90 days

29.4K1 year

Compare downloads with other packages →

Also on461 r2u33 autocran2.4K conda_forge59 c2d4u

Repository

GitHub ↗ patperry/r-mbest

26Stars

7Forks

5Open issues

0Open PRs

0Releases

184Commits

11Contributors

License Apache-2.0 · 184 commits · Last activity 2025-04-23

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/patperry/r-mbest on 2026-07-19.

Continuous integration (2)

Travis CIAppVeyor

Reproducibility and dev environment (1)

Makefile

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

7 external dependencies (excludes base and recommended)

Depends (2)

R >= 3.3.0nlme

Imports (5)

abind bigmemory foreach reformulas logging

LinkingTo (0)

none

Suggests (2)

testthat lme4

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

1direct

0indirect

skpr

Code & Tests

Code Composition

R 4,729 (87%)Rd 580 (11%)C 141 (3%)

Code characteristics

Object systems

S334

Cyclomatic complexity: 4.0 median / 40 max
Test cases: 37 / 0.24 per code line

Test coverage

Line coverage

76%

Expression

75.4%

Tests / Examples

76.4% / 59% ex

Functions

84 14 exported

Complexity

6 avg / 40 max

Call network

84 nodes / 50 edges

Call graph

Open call graph →

Loading call graph…

Lowest coverage

84 functions

Function	Cyclo	Coverage
backtrack	8	0%
backtrack.control	8	0%
blindsearch	7	0%
blindsearch.control	1	0%
print.VarCorr.mhglm	6	0%
print.backtrack	2	0%

People & History

People (5)

Maintainer (1)

Ben Bolker

Maintainer · added in 0.6.1

Authors (2)

Patrick O. Perry

Author

Ningshan Zhang

Author, Contributor · added in 0.6

Contributors (3)

Ningshan Zhang

Author, Contributor · added in 0.6

Kyle Schmaus

Contributor · added in 0.6

Timothy Sweetser

Contributor · added in 0.5

Listed in earlier versions (1)

Patrick O.

no longer listed · 0.5 to 0.6.1

Package Timeline

6 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
0.6.1Latest
2025-04-24 · current release · diff ↗
unarchivedReturned to CRAN
2025-04-24
R
R 4.5.0 released · 2025-04-11
archivedRemoved from CRAN
2025-03-10
issues were not corrected despite reminders
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
0.6
2018-05-25 · diff ↗
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
0.5
2016-03-08 · diff ↗

Show 5 earlier events

0.4
2015-10-19 · diff ↗
0.3
2015-04-20 · diff ↗
R
R 3.2.0 released · 2015-04-16
0.1
2014-06-05
R
R 3.1.0 released · 2014-04-10

Package metadata

First published: 2014-06-05
Total releases: 6 / 12 yrs
License: Apache License (== 2.0) | file LICENSE
Minimum R: ≥ 3.3.0
Download size: 150 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Mixed, Multilevel, and Hierarchical Models in R

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