glmm
glmm: mixed models from an R-style formula, with NumPy as the only dependency.
glmm fits mixed models in Rust, Python and R, and in the browser through WASM. One fit
covers ordinary least squares, generalized linear models, linear mixed models and
generalized linear mixed models.
- Accuracy first. Gives the same or a more accurate result than lme4, glmmTMB, MixedModels.jl and GLMMadaptive, and converges on every model that has a solution.
- Multi-solver. Uses a multi-solver paradigm to get the best result more robustly: closed form for least squares, IRLS for GLMs, and BFGS or BOBYQA for mixed models, all written from scratch in Rust.
- Fast. Faster than every other engine on every model, usually 10 to 100 times, without RAM blowup.
On all tested models: a 794-model validation grid, checked for every release.
Install
pip install glmm
Requires Python 3.10+. The only runtime dependency is NumPy.
Quick examples
df is any data table: a dict of columns, or a pandas / polars DataFrame.
import glmm
# OLS: fixed effects only
fit = glmm.fit(df, "y ~ x1 * x2")
# LMM: correlated random intercept and slope (REML)
fit = glmm.fit(df, "y ~ x1 + (1 + x1 | subject)")
# GLMM: binomial with a probit link, 7-node adaptive quadrature
fit = glmm.fit(df, "passed ~ x1 + (1 | school)", "binomial", link="probit", nagq=7)
fit.summary() # coefficient table + variance components
fit.beta, fit.se # estimates and standard errors
fit.converged, fit.singular # result flags
Documentation
Full walkthrough — every knob, the Fit object, and warm starts:
tutorial-python.md.
The algorithm map (dispatch graph, solver paths, tuning knobs) is traced to
code in
documentation/algorithms.md.
What the formula accepts:
formula.md.
Fixes for common errors:
troubleshooting.md.
Citation
If you use glmm in research, please cite:
Lenartowicz, P. (2026). glmm: Mixed-model fitting in Rust, Python and R [Computer software]. https://github.com/pawlenartowicz/glmm
@software{glmm2026,
author = {Lenartowicz, Pawe{\l}},
title = {{glmm}: Mixed-Model Fitting in Rust, Python and R},
year = {2026},
url = {https://github.com/pawlenartowicz/glmm}
}
License
LGPL-3.0-or-later.
Paweł Lenartowicz — Freestyler Scientist · GitHub · ORCID
Metadata
Release files for glmm 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| glmm-0.5.0.tar.gz | 1.7 MB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| glmm-0.5.0-cp310-abi3-win_amd64.whl | CPython 3.10 | abi3 | Windows x86-64 | Details |
| glmm-0.5.0-cp310-abi3-manylinux_2_28_x86_64.whl | CPython 3.10 | abi3 | Linux glibc 2.28+ x86-64 | Details |
| glmm-0.5.0-cp310-abi3-macosx_11_0_arm64.whl | CPython 3.10 | abi3 | macOS 11.0+ ARM64 | Details |
Total release size: 11.7 MB
Release files / glmm-0.5.0.tar.gz
| Download URL | glmm-0.5.0.tar.gz |
|---|---|
| Size | 1.7 MB |
| Tags | Source |
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| Size | 3.7 MB |
| Tags | CPython 3.10 Linux glibc 2.28+ x86-64 abi3 |
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