pblm
0.1-12Bivariate Additive Marginal Regression for Categorical Responses
Overview
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
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 84%
- Return-value docs
- 100%
- References docs
- 18%
Downloads
Repository
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Checks run against github.com/marcoenea/pblm on 2026-08-23.
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Dependencies
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Code & Tests
Datasets
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1-12Latest2026-03-10 · current release
- RR 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
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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