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Fit penalized splines mixed-effects models (a special case of additive models) for large longitudinal datasets. The package includes a psme() function that (1) relies on package 'mgcv' for constructing population and subject smooth functions as penalized splines, (2) transforms the constructed additive model to a linear mixed-effects model, (3) exploits package 'lme4' for model estimation and (4) backtransforms the estimated linear mixed-effects model to the additive model for interpretation and visualization. See Pedersen et al. (2019) <doi:10.7717/peerj.6876> and Bates et al. (2015) <doi:10.18637/jss.v067.i01> for an introduction. Unlike the gamm() function in 'mgcv', the psme() function is fast and memory-efficient, able to handle datasets with millions of observations.
Version: | 1.0.0 |
Depends: | R (≥ 4.0.0) |
Imports: | stats, Matrix, methods, mgcv, lme4 |
Published: | 2025-10-09 |
DOI: | 10.32614/CRAN.package.psme (may not be active yet) |
Author: | Zheyuan Li |
Maintainer: | Zheyuan Li <zheyuan.li at bath.edu> |
License: | GPL-3 |
URL: | https://github.com/ZheyuanLi/psme |
NeedsCompilation: | no |
CRAN checks: | psme results |
Reference manual: | psme.html , psme.pdf |
Package source: | psme_1.0.0.tar.gz |
Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): psme_1.0.0.tgz, r-oldrel (x86_64): psme_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.