galamm
0.4.0Generalized Additive Latent and Mixed Models
Overview
Estimates generalized additive latent and mixed models using maximum marginal likelihood, as defined in Sorensen et al. (2023) doi:10.1007/s11336-023-09910-z, which is an extension of Rabe-Hesketh and Skrondal (2004)'s unifying framework for multilevel latent variable modeling doi:10.1007/BF02295939. Efficient computation is done using sparse matrix methods, Laplace approximation, and automatic differentiation. The framework includes generalized multilevel models with heteroscedastic residuals, mixed response types, factor loadings, smoothing splines, crossed random effects, and combinations thereof. Syntax for model formulation is close to 'lme4' (Bates et al. (2015) doi:10.18637/jss.v067.i01) and 'PLmixed' (Rockwood and Jeon (2019) doi:10.1080/00273171.2018.1516541).
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- 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
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- NOTE2026-03-1011 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
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- Documented parameters
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- Return-value docs
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- References docs
- 38%
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Package metadata
- First published
- 2023-10-09
- Total releases
- 8 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 598 KB / 9 files
- Download size
- 4.8 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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