SAMM
1.1.1Some Algorithms for Mixed Models
Overview
This program can be used to fit Gaussian linear mixed models (LMM). Univariate and multivariate response models, multiple variance components, as well as, certain correlation and covariance structures are supported. In many occasions, the user can pick one of the several mixed model fitting algorithms, which are explained further in the details section. Some algorithms are specific to certain types of models (univariate or multivariate, diagonal or non-diagonal residual, one or multiple variance components, etc,...).
Install
Health
CRAN check results are not tracked yet.
Documentation
- Examples that run
- 25%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- References docs
- 25%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
4 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.4.0 released · 2024-04-24
- archivedRemoved from CRAN2024-04-20issues were not corrected despite reminders
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 1.1.12018-12-06 · diff ↗
- 1.12018-11-26 · diff ↗
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 0.0.12016-07-10 · diff ↗
- 0.02016-05-12
- RR 3.3.0 released · 2016-05-03
Package metadata
- Total releases
- 4
- License
- GPL-3 OSI
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("SAMM")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.
From data release v2026-08-11, which the citation names so these numbers can be found later. More on citing and the projects behind them.