MBRM
0.1.1Mixed Regression Models with Generalized Log-Gamma Random Effects
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Overview
About
Multivariate distribution derived from a Bernoulli mixed model under a marginal approach, incorporating a non-normal random intercept whose distribution is assumed to follow a generalized log-gamma (GLG) specification under a particular parameter setting. Estimation is performed by maximizing the log-likelihood using numerical optimization techniques (Lizandra C. Fabio, Vanessa Barros, Cristian Lobos, Jalmar M. F. Carrasco, Marginal multivariate approach: A novel strategy for handling correlated binary outcomes, 2025, under submission).
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Check history
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
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- Examples that run
- 83%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 33%
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Dependencies
Declared dependencies
6 external dependencies (excludes base and recommended)
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R >= 3.5
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Package Timeline
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.1Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
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Package metadata
- First published
- 2025-12-22
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 5.7 KB / 2 files
- Download size
- 17 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet