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glmmLasso (version 1.6.3)

Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation

Description

A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided, see Groll and Tutz (2014) . See also Groll and Tutz (2017) for discrete survival models including heterogeneity.

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Version

Install

install.packages('glmmLasso')

Monthly Downloads

770

Version

1.6.3

License

GPL-2

Maintainer

Andreas Groll

Last Published

August 23rd, 2023

Functions in glmmLasso (1.6.3)

glmmLasso

Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation.
knee

Clinical pain study on knee data
glmmLassoControl

Control Values for glmmLasso fit
acat

Family Object for Ordinal Regression with Adjacent Categories Probabilities
cumulative

Family Object for Ordinal Regression with Cumulative Probabilities
soccer

German Bundesliga data for the seasons 2008-2010