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splmm (version 1.1.2)

Simultaneous Penalized Linear Mixed Effects Models

Description

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 Unpublished thesis.

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Version

Install

install.packages('splmm')

Monthly Downloads

221

Version

1.1.2

License

GPL-3

Maintainer

Luoying Yang

Last Published

November 22nd, 2020

Functions in splmm (1.1.2)

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