R Observatory: Metrics for ProfileGLMM version 1.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

ProfileGLMM

1.1.0

Bayesian Profile Regression using Generalised Linear Mixed Models

0packages depend

2Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Matteo AmestoyCRAN page ↗GitHub ↗Issues ↗

Implements a Bayesian profile regression using a generalized linear mixed model as output model. The package allows for binary (probit mixed model) and continuous (linear mixed model) outcomes and both continuous and categorical clustering variables. The package utilizes 'RcppArmadillo' and 'RcppDist' for high-performance statistical computing in C++. For more details see Amestoy & al. (2025) doi:10.48550/arXiv.2510.08304.

Changes in 1.1.0

profileGLMM_Gibbs and profileGLMM_preProcess now output S3 classes and some generic methods have been implemented
Added an introduction vignette

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("ProfileGLMM", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("MatteoAmestoy/ProfileGLMM-package")

Development version from MatteoAmestoy/ProfileGLMM-package. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-profileglmm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-ProfileGLMM

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-ProfileGLMM

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 25.1 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-20
ERROR12 OK, 1 ERROR2026-08-15
OK13 OK2026-08-05

Show 7 earlier changesHide 7 earlier changes

NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-07-03
ERROR12 OK, 1 ERROR2026-07-01
OK12 OK2026-04-25
NOTE12 OK, 2 NOTE2026-04-22
ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
NOTE12 OK, 2 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.1.0

READMEYes · 87 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 1.1.0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 15
Examples that run: 100%7 run in a plain check
Exported functions with examples: 100%
Documented parameters: 94%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

Introduction to ProfileGLMM HTML

How these are measured

Downloads

2K

CRAN downloads in the past year

Rank #22,060 · ~5/day · ~163/mo

Releases R versions

Daily download trend is not available in this view yet.

23530 days

58290 days

2K1 year

Compare downloads with other packages →

Also on283 r2u5 autocran

How downloads are counted

Repository

matteoamestoy/profileglmm-package ↗Account: MatteoAmestoy

0Stars

0Forks

3Open issues

0Open PRs

0Releases

Last activity 2026-02-03

Responsiveness

not measured

Issues over time

2026-07-07 · 22026-08-31 · 3

How these are measured

PracticesBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/matteoamestoy/profileglmm-package on 2026-10-11.

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

10 external dependencies (excludes base and recommended)

Installing ProfileGLMM adds 35 packages (21 with compiled code, 29 MB of source tarballs). Heaviest: ggplot2 6.0 MB, Spectrum 3.6 MB, LaplacesDemon 2.0 MB.

Depends (1)

R >= 3.5

Imports (6)

Rcpp LaplacesDemon MCMCpackMatrixSpectrum mvtnorm

LinkingTo (3)

Rcpp RcppArmadillo RcppDist

Suggests (2)

knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (3)

Matteo Amestoy

Wessel van Wieringen

Thesis advisor

Mark van de Wiel

Thesis advisor

Releases (2)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
1.1.0Latest
record
2026-02-03 · current release · diff ↗ ·
removed 1 export
profileGLMM_predict
1.0.2
record
2025-12-18
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-12-18
Total releases: 2 / 1 yrs
License: GPL-2 OSI
Minimum R: ≥ 3.5
Bundled data: 1.1 MB / 3 files
Download size: 1.1 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ProfileGLMM")

Format

Amestoy, M., van Wieringen, W., & van de Wiel, M. (2026). ProfileGLMM: Bayesian Profile Regression using Generalised Linear Mixed Models (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.ProfileGLMM

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ProfileGLMM version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-10-17. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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