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pblm

0.1-12Package record

Bivariate Additive Marginal Regression for Categorical Responses

0packages depend
1.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Bivariate additive categorical regression via penalized maximum likelihood. Under a multinomial framework, the method fits bivariate models where both responses are nominal, ordinal, or a mix of the two. Partial proportional odds models are supported, with flexible (non-)uniform association structures. Various logit types and parametrizations can be specified for both marginals and the association, including Dale’s model. The association structure can be regularized using polynomial-type penalty terms. Additive effects are modeled using P-splines. Standard methods such as summary(), residuals(), and predict() are available.

Install

Health

CRAN checks
13OK
Slowest check: 2.2 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1-12
READMENoVignettesNoNEWSNoCitation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
11includes a package overview page
Examples that run
100%9 run in a plain check
Exported functions with examples
88%
Documented parameters
84%
Return-value docs
100%
Help pages citing references
18%

Downloads

1.8K
CRAN downloads in the past year
Rank #24,069 · ~5/day · ~152/mo
Daily download trend is not available in this view yet.
20030 days
50990 days
1.8K1 year
Compare downloads with other packages →
Also on68 r2u

Repository

0Stars
0Forks
0Open issues
0Open PRs
1Releases
8Commits
1Commit identities
dale-modelbivariate-logistic-modelbivariate-ordered-modelsemiparametricadditivemaximum-likelihood-estimationpenalty-termsmoothing
8 commits · Last activity 2020-02-06
Responsiveness
not measured

Releases over time

2020-02-06 · 12026-07-07 · 1
PracticesBeta

Checks run against github.com/marcoenea/pblm on 2026-10-11.

No development-tooling practices detected in the upstream repository.

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

Dependencies

Declared dependencies
0 external dependencies (excludes base and recommended)

Installing pblm adds no packages beyond those that come with R.

Depends (5)
R >= 4.4.0MatrixlatticesplinesMASS
Imports (1)
methods
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (3)
Author, Maintainer since 0.1-12 (2025), Copyright holder
Contributor
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 0.1-12Latest
    2025-06-19 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-06-19
Total releases
1 / 1 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 4.4.0
Bundled data
0.8 KB / 2 files
Download size
51 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("pblm")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1177/1471082x18782063.

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 pblm version 0.1-12 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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