This function computes crossvalidated tuning parameter value for longitudinal data with working independence structure.
1 2 
formula 
A formula expression in the form of 
id 
A vector for identifying subjects/clusters. 
data 
A data frame which stores the variables in 
scale.fix 
A logical variable; if true, the scale parameter is fixed at the value of 
scale.value 
If 
family 
A 
fold 
The number of folds used in crossvalidation. 
lambda.vec 
A vector of tuning parameters that will be used in the crossvalidation. 
pindex 
An index vector showing the parameters which are not subject to penalization. The default value
is 
eps 
A numerical value for the epsilon used in minorizationmaximization algorithm. The default value is

maxiter 
The number of iterations that is used in the estimation algorithm. The default value is 
tol 
The tolerance level that is used in the estimation algorithm. The default value is 
An object class of CVfit
.
Wang, L., Zhou, J., and Qu, A. (2012). Penalized generalized estimating equations for highdimensional longitudinal data analysis. Biometrics, 68, 353–360.
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