# splmm v1.1.2

0

0th

Percentile

## 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 Unpublished thesis.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!