Skip to content

Reparameterized Regression Models

0packages depend
2.6Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Changes in 1.4
  • functions fit.RLL.cens was added

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.2 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.4
READMENoVignettesNoNEWSYes · 100% structured · mentions 1.4Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
8
Examples that run
100%8 run in a plain check
Exported functions with examples
100%
Documented parameters
62%
Return-value docs
100%
Help pages citing references
100%

Downloads

2.6K
CRAN downloads in the past year
Rank #15,720 · ~7/day · ~217/mo
Daily download trend is not available in this view yet.
30130 days
79090 days
2.6K1 year
Compare downloads with other packages →
Also on67 r2u2 autocran

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)

Installing rregm adds 16 packages (6 with compiled code, 10 MB of source tarballs). Heaviest: invgamma 2.5 MB, Rcpp 1.8 MB, gamlss.dist 1.5 MB.

Depends (2)
R >= 4.0.0stats
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (5)
Author, Maintainer since 1.0 (2026)
Contributor · added in 1.2
Contributor · added in 1.2
Releases (5)

Pick two releases to compare their code metrics.

  • 1.4Latest
    record
    2026-09-05 · current release · diff ↗ ·
    added 1 export
    fit.RLL.cens
  • 1.3
    record
    2026-07-21 · diff ↗ ·
    added 109 exports
    BPAM, BPGM, BPHM, BPMD, BPMO, dBPAM, dBPGM, dBPHM, dBPMD, dBPMO, dGAM, dGGM, dGHM, dGMD, dGMO, dLL, dLL2, dLL3, dLL4, dLL5, dLL6, dLNAM, dLNGM, dLNHM, dLNMD, dLNMO, dRLL, fit.RLL, GAM, GGM and 79 more
  • 1.2
    record
    2026-06-08 · diff ↗ ·
    added 2 exports
    RBE.predictive, RBE.skovgaard
  • R
    R 4.6.0 released · 2026-04-24
  • 1.1
    record
    2026-04-10 · diff ↗ ·
    added 5 exports
    fit.RLN, dRLN, pRLN, qRLN, rRLN
  • 1.0
    record
    2026-01-28
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-28
Total releases
5 / 1 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 4.0.0
Download size
54 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("rregm")
Gallardo, D., Bourguignon, M., Brandao, M., Izbicki, R., & Magalhaes, T. (2026). rregm: Reparameterized Regression Models (Version 1.4) [Computer software]. https://doi.org/10.32614/CRAN.package.rregm

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 rregm version 1.4 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →

Privacy choices

These apply to this browser and are stored on this device only. Nothing about your choice is sent to us.

Read the privacy policy