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 Unpublished thesis.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:
splmm_1.2.0.tar.gz
splmm_1.2.0.tar.gz(r-4.5-noble)splmm_1.2.0.tar.gz(r-4.4-noble)
splmm_1.2.0.tgz(r-4.4-emscripten)splmm_1.2.0.tgz(r-4.3-emscripten)
splmm.pdf |splmm.html✨
splmm/json (API)
| # Install 'splmm' in R: |
| install.packages('splmm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- cognitive - Kenya School Lunch Intervention Cognitive Dataset
- simulated_data - Dataset simulated for toy example
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:7d91b0f817. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 12 2024 |
| R-4.5-linux-x86_64 | OK | Sep 12 2024 |
Exports:plot.splmmplot3D.splmmprint.splmmsplmmsplmm.defaultsplmmControlsplmmTuningsummary.splmm
Dependencies:clicolorspacecrayondigestemulatorfansifarverggplot2gluegridExtragtablehmsisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmisc3dmiscToolsmunsellmvtnormnlmepenalizedpillarpkgconfigplot3DprettyunitsprogressR6RColorBrewerRcppRcppArmadillorlangscalessurvivaltibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Simultaneous Penalized Linear Mixed Effects Models | splmm-package |
| Kenya School Lunch Intervention Cognitive Dataset | cognitive |
| Plot the tuning results of a 'splmm.tuning' object | plot.splmm |
| 3D Plot the tuning results of a ''splmm.tuning'' object when tuning over both lambda 1 and lambda 2 grids | plot3D.splmm |
| Print a short summary of a splmm object. | print.splmm |
| Dataset simulated for toy example | simulated_data |
| Function to fit linear mixed-effects model with double penalty for fixed effects and random effects | splmm splmm.default |
| Options for the 'splmm' Algorithm | splmmControl |
| Tuning funtion of ''splmm'' object | splmmTuning |
| Summarize an 'splmm' object | summary.splmm |