Gradient Boosting for Generalized Additive Mixed Models
Overview
Provides a novel framework to estimate mixed models via gradient boosting. The implemented functions are based on the 'mboost' and 'lme4' packages, and the family range is therefore determined by 'lme4'. A correction mechanism for cluster-constant covariates is implemented, as well as estimation of the covariance of random effects. These methods are described in the accompanying publication; see doi:10.1007/s11222-025-10612-y for details.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 8
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Dependencies
Installing mermboost adds 33 packages (23 with compiled code, 41 MB of source tarballs). Heaviest: stringi 11 MB, data.table 5.7 MB, lme4 4.3 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2025-02-24
- Total releases
- 3 / 1 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 30 KB / 3 files
- Download size
- 52 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("mermboost")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1007/s11222-025-10612-y.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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.