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Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. The details of the algorithm can be found in Luoying Yang PhD thesis (Yang and Wu 2020). The algorithm implementation is based on the R package 'lmmlasso'. Reference: Yang L, Wu TT (2020). Model-Based Clustering of Longitudinal Data in High-Dimensionality. Unpublished thesis.
Version: | 1.2.0 |
Depends: | R (≥ 3.5.0) |
Imports: | Rcpp (≥ 1.0.1), emulator, miscTools, penalized, ggplot2, gridExtra, plot3D, MASS, progress, methods |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2024-06-13 |
DOI: | 10.32614/CRAN.package.splmm |
Author: | Luoying Yang [aut], Eli Sun [aut, cre], Tong Tong Wu [aut] |
Maintainer: | Eli Sun <eli_sun at urmc.rochester.edu> |
License: | GPL-3 |
NeedsCompilation: | yes |
In views: | MixedModels |
CRAN checks: | splmm results |
Reference manual: | splmm.pdf |
Package source: | splmm_1.2.0.tar.gz |
Windows binaries: | r-devel: splmm_1.2.0.zip, r-release: splmm_1.2.0.zip, r-oldrel: splmm_1.2.0.zip |
macOS binaries: | r-release (arm64): splmm_1.2.0.tgz, r-oldrel (arm64): splmm_1.2.0.tgz, r-release (x86_64): splmm_1.2.0.tgz, r-oldrel (x86_64): splmm_1.2.0.tgz |
Old sources: | splmm archive |
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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.