geeVerse
is an R package to provide computationally
efficient implementations of penalized generalized estimating equations
for any combination of 1) simultaneous variable selection and estimation
for high and even ultra-high dimensional data, 2) conditional quantile
or mean regression, and 3) longitudinal or cross-sectional data
analysis.
You can install the latest version of geeVerse
from
GitHub with:
# install.packages("devtools")
::install_github("zzz1990771/geeVerse") devtools
After installation, you can load the package as usual:
library(geeVerse)
To get detailed documentation on the qpgee
function,
use:
?qpgee
This will show you the function’s usage, arguments, and examples.
Running an Example:
#settings
<- generateData(nsub = 20, nobs = rep(10, 20), p = 20,
sim_data beta0 = c(rep(1,5),rep(0,15)), rho = 0.1, correlation = "AR1",
dis = "normal", ka = 1)
=sim_data$X
X=sim_data$y
y
#fit qpgee with auto selected lambda
= qpgee(X,y,tau=0.5,nobs=rep(10, 20),ncore=1)
qpgee.fit $beta qpgee.fit