The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

geeVerse

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.

Installation

You can install the latest version of geeVerse from GitHub with:

# install.packages("devtools")
devtools::install_github("zzz1990771/geeVerse")

Usage and Example:

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
sim_data <- generateData(nsub = 20, nobs = rep(10, 20),  p = 20,
                         beta0 = c(rep(1,5),rep(0,15)), rho = 0.1, correlation = "AR1",
                          dis = "normal", ka = 1)

X=sim_data$X
y=sim_data$y

#fit qpgee with auto selected lambda
qpgee.fit = qpgee(X,y,tau=0.5,nobs=rep(10, 20),ncore=1)
qpgee.fit$beta

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.