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bml

0.9.0

Bayesian Multiple-Membership Multilevel Models with Parameterizable Weight Functions

0packages depend
1.5Kdownloads / year
86.6%test coverage
13/13checks pass

Overview

About
Maintained by Benjamin RoscheFirst published 2026-02-201 releasesCRAN page ↗GitHub ↗

Implements Bayesian multiple-membership multilevel models with parameterizable weight functions via 'JAGS' to model how lower-level units jointly shape higher-level outcomes (micro-macro link) across a range of outcome types (e.g., linear, logit, and survival models). Supports estimation and comparison of alternative aggregation mechanisms, allows weight matrices to be endogenized through parameters and covariates, and accommodates complex dependence structures that extend beyond traditional multilevel frameworks. For details, see Rosche (2026) "A Multilevel Model for Coalition Governments. Uncovering Party-Level Dependencies Within and Between Governments" doi:10.31235/osf.io/4bafr_v2.

Install

Health

CRAN checks
13OK
Slowest check: 3.2 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.67
86.6%
Coverage · measured lines
100%
Documentation · exports
12
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 776 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
8%
Documented parameters
99%
Return-value docs
100%
References docs
50%

Downloads

1.5K
CRAN downloads in the past year
Rank #16,627 · ~4/day · ~124/mo
Daily download trend is not available in this view yet.
14730 days
63990 days
1.5K1 year
Compare downloads with other packages →
Also on46 r2u27 autocran

Repository

Repository
6Stars
2Forks
0Open issues
1Open PRs
0Releases
150Commits
4Contributors
150 commits · Last activity 2026-08-04 · 0% stars, 30d

Stars over time

2024-05-01 · 52026-07-07 · 6

Repository practices

Upstream repositoryBeta

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

Checks run against github.com/benrosche/bml on 2026-08-16.

Continuous integration (1)
GitHub Actions
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
16 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.9.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-02-20
Total releases
1 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1.0
Bundled data
38 KB / 1 file
Download size
455 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("bml")
Rosche, B. (2026). bml: Bayesian Multiple-Membership Multilevel Models with Parameterizable Weight Functions (Version 0.9.0) [Computer software]. https://doi.org/10.32614/CRAN.package.bml

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for bml version 0.9.0 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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