LMMsolver
1.0.13Linear Mixed Models with Sparse Matrix Methods and Smoothing
Overview
Provides tools for fitting linear mixed models using sparse matrix methods and variance component estimation. Applications include spline-based modeling of spatial and temporal trends using penalized splines (Boer, 2023) doi:10.1177/1471082X231178591.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2211 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1810 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
- NOTE2026-03-1011 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 93%
- Documented parameters
- 94%
- Return-value docs
- 100%
- References docs
- 26%
Downloads
Repository
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Repository practices
5 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/biometris/lmmsolver on 2026-08-16.
Dependencies
Code & Tests
Datasets
People & History
14 releases. Pick two to compare their code metrics. R releases are shown for context.
- 1.0.13Latest
- RR 4.6.0 released · 2026-04-24
- 1.0.122025-12-05 · diff ↗
- 1.0.112025-08-20 · diff ↗
- 1.0.102025-05-14 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 1.0.92025-01-14 · diff ↗
- 1.0.82024-08-26 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 1.0.72024-04-16 · diff ↗
- 1.0.62023-11-27 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 1.0.52023-04-14 · diff ↗
- 1.0.42022-12-15 · diff ↗
- 1.0.32022-08-19 · diff ↗
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2021-11-02
- Total releases
- 14 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.6
- Bundled data
- 126 KB / 5 files
- Download size
- 7.1 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("LMMsolver")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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