EW_Fi_MLM_func: Function to generate the Expectation of fisher information at...

In ForLion: 'ForLion' Algorithm to Find D-Optimal Designs for Experiments

Function to generate the Expectation of fisher information at one design point xi for multinomial logit models

Description

Function to generate the Expectation of fisher information at one design point xi for multinomial logit models

Usage

EW_Fi_MLM_func(X_x, bvec_matrix, link = "continuation")

Arguments

X_x	model matrix for a specific design point x_i, X_x=h.func(xi)
bvec_matrix	the matrix of the bootstrap parameter values of beta
link	multinomial logit model link function name "baseline", "cumulative", "adjacent", or"continuation", default to be "continuation"

Value

F_x Fisher information matrix at x_i

EU_x U matrix for calculation the Expectation of Fisher information matrix at x_i

Examples

link.temp = "continuation"
xi.temp=c(80)
hfunc.temp = function(y){
matrix(data=c(1,y,y*y,0,0,0,0,0,1,y,0,0,0,0,0), nrow=3, ncol=5, byrow=TRUE)
}
X_xtemp=hfunc.temp(xi.temp)
bvec_bootstrap<-matrix(c(-0.2401, -1.9292, -2.7851, -1.614,-1.162,
                         -0.0535, -0.0274, -0.0096,-0.0291, -0.04,
                          0.0004,  0.0003,  0.0002,  0.0003,  0.1,
                         -9.2154, -9.7576, -9.6818, -8.5139, -8.56),nrow=4,byrow=TRUE)
EW_Fi_MLM_func(X_x=X_xtemp, bvec_matrix=bvec_bootstrap, link=link.temp)

ForLion documentation built on April 11, 2025, 5:38 p.m.