splmm v1.1.2
0
Monthly downloads
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 Unpublished thesis.
Functions in splmm
| Name | Description | |
| summary.splmm | Summarize an 'splmm' object | |
| splmmControl | Options for the 'splmm' Algorithm | |
| splmmTuning | Tuning funtion of 'splmm' object | |
| splmm | Function to fit linear mixed-effects model with double penalty for fixed effects and random effects | |
| splmm-package | splmm | |
| print.splmm | Print a short summary of a splmm object. | |
| plot3D.splmm | 3D Plot the tuning results of a 'splmm.tuning' object when tuning over both lambda 1 and lambda 2 grids | |
| plot.splmm | Plot the tuning results of a splmm.tuning object | |
| cognitive | Kenya School Lunch Intervention Cognitive Dataset | |
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2020-11-20 |
| License | GPL-3 |
| LinkingTo | Rcpp, RcppArmadillo |
| NeedsCompilation | yes |
| Packaged | 2020-11-21 00:53:19 UTC; lyang19 |
| Repository | CRAN |
| Date/Publication | 2020-11-22 00:00:02 UTC |
| imports | emulator , ggplot2 , gridExtra , MASS , miscTools , penalized , plot3D , Rcpp (>= 1.0.1) |
| depends | R (>= 3.5.0) |
| linkingto | RcppArmadillo |
| Contributors | Tong Wu, Luoying Yang |
Include our badge in your README
[](http://www.rdocumentation.org/packages/splmm)