fastFMM: Fast Functional Mixed Models using Fast Univariate Inference (original) (raw)
Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2024) <doi:10.7554/eLife.95802.2>) for fitting functional mixed models. User guides and Python package information can be found at <https://github.com/gloewing/photometry_FLMM>.
| Version: | 0.4.0 |
|---|---|
| Imports: | lme4, parallel, cAIC4, magrittr, dplyr, mgcv, MASS, lsei, refund, stringr, Matrix, mvtnorm, progress, ggplot2, gridExtra, Rfast, lmeresampler, stats, methods |
| Suggests: | knitr, rmarkdown, spelling |
| Published: | 2025-03-13 |
| DOI: | 10.32614/CRAN.package.fastFMM |
| Author: | Erjia Cui [aut, cre], Gabriel Loewinger [aut], Al Xin [ctb] |
| Maintainer: | Erjia Cui |
| BugReports: | https://github.com/gloewing/fastFMM/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/gloewing/fastFMM |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README, NEWS |
| In views: | FunctionalData |
| CRAN checks: | fastFMM results |
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