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.">

psme: Penalized Splines Mixed-Effects Models (original) (raw)

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
Author: Zheyuan Li ORCID iD [aut, cre]
Maintainer: Zheyuan Li <zheyuan.li at bath.edu>
License: GPL-3
URL: https://github.com/ZheyuanLi/psme
NeedsCompilation: no
CRAN checks: psme results

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