rregm: Reparameterized Regression Models
Provides estimation and data generation tools for several new regression models,
including the gamma, beta, inverse gamma, beta prime, log-normal and log-logistic
distributions. These models can be parameterized based on the mean, median, mode,
geometric mean and harmonic mean, except for the log-logistic model which is based
on alternative parametrizations.
For details, see Bourguignon and Gallardo (2025a) <doi:10.1016/j.chemolab.2025.105382> and
Bourguignon and Gallardo (2025b) <doi:10.1111/stan.70007>.
The package also implements higher-order likelihood inference through Skovgaard-adjusted
likelihood ratio statistics and predictive shrinkage estimators reparameterized
beta regression models.
| Version: |
1.3 |
| Depends: |
R (≥ 4.0.0), stats |
| Imports: |
extraDistr, pracma, gamlss, gamlss.dist, invgamma, skewMLRM |
| Published: |
2026-07-21 |
| DOI: |
10.32614/CRAN.package.rregm |
| Author: |
Diego Gallardo [aut, cre],
Marcelo Bourguignon [aut],
Marcia Brandao [aut],
Tiago Magalhaes [ctb],
Rafael Izbicki [ctb] |
| Maintainer: |
Diego Gallardo <dgallardo at ubiobio.cl> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
rregm results |
Documentation:
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