QIC: Calculate quasi-likelihood under the independence model...

In seqest: Sequential Method for Classification and Generalized Estimating Equations Problem

Description

Select the optimal model according to the QIC criterion

Usage

QIC(y, X, id, beta, nonZeroSet, rho, linkv, corstrv)

Arguments

y	A matrix containing current response variable
X	A data frame containing the covariate for the current samples
id	The id for each subject in the X
beta	The paramters that we estimate when we use the current samples
nonZeroSet	The set of the index of the non zero coefficient
rho	A numeric number indicating the estimate of correlation coefficient
linkv	A specification for the model link function.
corstrv	A character string specifying the correlation structure. The following are permitted: "independence", "exchangeable" and "ar1".

Details

QIC calculates the value of the quasi-likelihood under the independence model criterion for Generalized Estimating Equations. The QIC criterion is actually a generalization of the AIC criterion in the statistical inference of parameters in the longitudinal data analysis framework.

Value

a value indicating how well the model fits

seqest documentation built on July 2, 2020, 2:28 a.m.