Package: splmm 1.2.0

Eli Sun

splmm: Simultaneous Penalized Linear Mixed Effects Models

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 Unpublished thesis.

Authors:Luoying Yang [aut], Eli Sun [aut, cre], Tong Tong Wu [aut]

splmm_1.2.0.tar.gz
splmm_1.2.0.zip(r-4.7-x86_64)splmm_1.2.0.zip(r-4.7-arm64)splmm_1.2.0.zip(r-4.6-x86_64)splmm_1.2.0.zip(r-4.6-arm64)
splmm_1.2.0.tar.gz(r-4.7-arm64)splmm_1.2.0.tar.gz(r-4.7-x86_64)splmm_1.2.0.tar.gz(r-4.6-arm64)splmm_1.2.0.tar.gz(r-4.6-x86_64)
splmm_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
splmm/json (API)

# Install 'splmm' in R:
install.packages('splmm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.00 score 4 scripts 292 downloads 8 exports 37 dependencies

Last updated from:7d91b0f817. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK139
linux-devel-x86_64OK143
source / vignettesOK267
linux-release-arm64OK112
linux-release-x86_64OK141
windows-devel-arm64OK217
windows-devel-x86_64OK176
windows-release-arm64OK231
windows-release-x86_64OK147
wasm-releaseOK100

Exports:plot.splmmplot3D.splmmprint.splmmsplmmsplmm.defaultsplmmControlsplmmTuningsummary.splmm

Dependencies:clicpp11crayondigestemulatorfarverggplot2gluegridExtragtablehmsisobandlabelinglatticelifecycleMASSMatrixmisc3dmiscToolsmvtnormpenalizedpkgconfigplot3DprettyunitsprogressquadformR6RColorBrewerRcppRcppArmadillorlangS7scalessurvivalvctrsviridisLitewithr