D_optimal: Get the most informative subjects for the clustered data

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

Description

Get the most informative subjects for the highly stratified response data by the D-optimility.

Usage

D_optimal(X, id, beta, nonZeroSet, M, rho, linkv, corstrv)

Arguments

X	A data frame contains all the random samples which we will choose subject from.
id	The id for each subject in the X
beta	The paramters that we estimate under the current samples
nonZeroSet	The set of the index of the non zero coefficient
M	A numeric matrix calculated by the getMH function
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

D_optimal uses the D-optimality criterion from the experimental design to choose the most informative subjects for the highly stratified response data.

Value

a index of the most informative subject

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