Function to compute cross-validated tuning parameter value

Description

This function computes cross-validated tuning parameter value for longitudinal data with working independence structure.

Usage

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CVfit(formula, id, data, family, scale.fix, scale.value, fold, lambda.vec, pindex,  
eps, maxiter, tol)

Arguments

formula

A formula expression in the form of response ~ predictors.

id

A vector for identifying subjects/clusters.

data

A data frame which stores the variables in formula with id variable.

scale.fix

A logical variable; if true, the scale parameter is fixed at the value of scale.value. The default value is FALSE.

scale.value

If scale.fix = TRUE, this assignes a numeric value to which the scale parameter should be fixed.

family

A family object in PGEE.

fold

The number of folds used in cross-validation.

lambda.vec

A vector of tuning parameters that will be used in the cross-validation.

pindex

An index vector showing the parameters which are not subject to penalization. The default value is NULL. However, in case of a model with intercept, the intercept parameter should be never penalized.

eps

A numerical value for the epsilon used in minorization-maximization algorithm. The default value is 10^-6.

maxiter

The number of iterations that is used in the estimation algorithm. The default value is 25.

tol

The tolerance level that is used in the estimation algorithm. The default value is 10^-3.

Value

An object class of CVfit.

References

Wang, L., Zhou, J., and Qu, A. (2012). Penalized generalized estimating equations for high-dimensional longitudinal data analysis. Biometrics, 68, 353–360.

See Also

PGEE