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Multivariate Response Generalized Linear Models

0packages dependsuggested by 1
9.6Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Provides functions that (1) fit multivariate discrete distributions, (2) generate random numbers from multivariate discrete distributions, and (3) run regression and penalized regression on the multivariate categorical response data. Implemented models include: multinomial logit model, Dirichlet multinomial model, generalized Dirichlet multinomial model, and negative multinomial model. Making the best of the minorization-maximization (MM) algorithm and Newton-Raphson method, we derive and implement stable and efficient algorithms to find the maximum likelihood estimates. On a multi-core machine, multi-threading is supported.

Changes in 0.2.3
  • Updated inst/CITATION to use bibentry() and person() instead of the defunct citEntry() and personList().
  • Removed redundant \itemize{} wrappers inside \value{} sections of the documentation for MGLMfit(), MGLMreg(), MGLMsparsereg(), MGLMtune() and path(), which caused "lost braces" notes in R CMD check.
  • Reduced the size of the MGLMtune() and path() examples so that they run well within CRAN's example timing limits.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.5 min · r-release-macos-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-30
  • NOTE14 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.2.3
READMENoVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.2.3Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
27 (1 internal)includes a package overview page
Examples that run
100%22 run in a plain check
Exported functions with examples
82%
Documented parameters
76%
Return-value docs
82%
Help pages citing references
0%
Vignettes (1)

Downloads

9.6K
CRAN downloads in the past year
Rank #3,306 · ~26/day · ~798/mo
Daily download trend is not available in this view yet.
2.2K30 days
3.4K90 days
9.6K1 year
Compare downloads with other packages →
Also on127 r2u9 autocran2K conda_forge

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)

Installing MGLM adds no packages beyond those that come with R.

Depends (1)
R >= 3.0.0
Imports (4)
methodsstatsparallelstats4
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect
Suggested by 1
Suggests, most downloaded first

Datasets

People & History

People (4)
Maintainer · added in 0.2.3
Author
Contributor · added in 0.2.3

Maintainer since 0.0.9 (2018), previously Yiwen Zhang (0.0.1 to 0.0.8)

Releases (15)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • archivedRemoved from CRAN
    2015-03-03
    misuse of '\donttest' was not corrected
  • R
    R 3.1.0 released · 2014-04-10
  • 3.0.3Latest
    record
    2014-02-03 · current release · diff ↗
  • 3.0.2
    record
    2013-07-06 · diff ↗ ·
    added 13 exports
    pattern:^[[:alpha:]]+, ddirm, dgdirm, dmn, dnegmn, kr, MGLMfit, MGLMreg, MGLMsparsereg, MGLMtune, rdirm, rgdirm, rnegmn
Show 14 earlier eventsHide 14 earlier events

Package metadata

First published
2013-07-06
Total releases
15 / 13 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.0.0
Bundled data
3.9 KB / 1 file
Download size
72 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MGLM")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

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 MGLM version 0.2.3 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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