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pumBayes

1.0.2Package record

Bayesian Estimation of Probit Unfolding Models for Binary Preference Data

0packages depend
2.4Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Bayesian estimation and analysis methods for Probit Unfolding Models (PUMs), a novel class of scaling models designed for binary preference data. These models allow for both monotonic and non-monotonic response functions. The package supports Bayesian inference for both static and dynamic PUMs using Markov chain Monte Carlo (MCMC) algorithms with minimal or no tuning. Key functionalities include posterior sampling, hyperparameter selection, data preprocessing, model fit evaluation, and visualization. The methods are particularly suited to analyzing voting data, such as from the U.S. Congress or Supreme Court, but can also be applied in other contexts where non-monotonic responses are expected. For methodological details, see Shi et al. (2025) doi:10.48550/arXiv.2504.00423.

Install

Health

CRAN checks
13OK
Slowest check: 3.2 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-04-22
Show 2 earlier changesHide 2 earlier changes
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.2
READMEYes · 179 wordsVignettesNoNEWSNoCitation fileNo
Help pages
13
Examples that run
54%7 run in a plain check · 6 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
92%
Return-value docs
100%
Help pages citing references
0%

Downloads

2.4K
CRAN downloads in the past year
Rank #19,930 · ~7/day · ~199/mo
Daily download trend is not available in this view yet.
22430 days
66890 days
2.4K1 year
Compare downloads with other packages →
Also on377 r2u7 autocran

Repository

105Stars
0Forks
1Open issues
0Open PRs
2Releases
62Commits
3Commit identities
License file reads as GPL-3.0 · 62 commits · Last activity 2026-02-09 · +250% stars, 30d
Responsiveness
not measured

Stars over time

2025-09-14 · 142026-10-22 · 105
PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/skylarshihub/pumbayes on 2026-10-21.

Continuous integration (1)
GitHub Actions
Docs source (1)

GitHub Pages site last deployed 2026-02-09

CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)

Installing pumBayes adds 5 packages (5 with compiled code, 3.9 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, mvtnorm 1.0 MB.

Depends (1)
R >= 3.6.0
Imports (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (4)
Author, Maintainer since 1.0.0 (2025)
Copyright holder
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • unarchivedReturned to CRAN
    2026-02-09
  • 1.0.2Latest
    record
    2026-02-09 · current release · diff ↗
  • archivedRemoved from CRAN
    2026-01-25
    issues were not corrected in time gcc 14 warns, also C++20 issues
  • 1.0.1
    record
    2025-10-23 · diff ↗
  • 1.0.0
    record
    2025-05-30
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-05-30
Total releases
3 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 3.6.0
Bundled data
79 KB / 2 files
Download size
119 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("pumBayes")
Shi, S., Lei, R., Olmsted, J., & Rodriguez, A. (2026). pumBayes: Bayesian Estimation of Probit Unfolding Models for Binary Preference Data (Version 1.0.2) [Computer software]. https://doi.org/10.32614/CRAN.package.pumBayes

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for pumBayes version 1.0.2 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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