Bivariate 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
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- 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%
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Repository
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Dependencies
Installing pblm adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1-12Latest2025-06-19 · 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
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Run in R for the authors' entry:
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It points to 10.1177/1471082x18782063.
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