EW_liftoneDoptimal_MLM_func: function of EW liftone for multinomial logit model

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

function of EW liftone for multinomial logit model

Description

function of EW liftone for multinomial logit model

Usage

EW_liftoneDoptimal_MLM_func(
  m,
  p,
  Xi,
  J,
  thetavec_matrix,
  link = "continuation",
  reltol = 1e-05,
  maxit = 500,
  p00 = NULL,
  random = FALSE,
  nram = 3
)

Arguments

m	number of design points
p	number of parameters in the multinomial logit model
Xi	model matrix
J	number of response levels in the multinomial logit model
thetavec_matrix	the matrix of the sampled parameter values of beta
link	multinomial logit model link function name "baseline", "cumulative", "adjacent", or"continuation", default to be "continuation"
reltol	relative tolerance for convergence, default to 1e-5
maxit	the number of maximum iteration, default to 500
p00	specified initial approximate allocation, default to NULL, if NULL, will generate a random initial approximate allocation
random	TRUE or FALSE, if TRUE then the function will run lift-one with additional "nram" number of random approximate allocation, default to be FALSE
nram	when random == TRUE, the function will run lift-one nram number of initial proportion p00, default is 3

Value

p reported EW D-optimal approximate allocation

p0 the initial approximate allocation that derived the reported EW D-optimal design

Maximum the maximum of the determinant of the expected Fisher information matrix

Convergence TRUE or FALSE, whether the algorithm converges

itmax maximum iterations

Examples

m=7
p=5
J=3
link.temp = "continuation"
factor_x=c(80,100,120,140,160,180,200)
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)
}
Xi=rep(0,J*p*m); dim(Xi)=c(J,p,m)
for(i in 1:m) {
Xi[,,i]=hfunc.temp(factor_x[i])
}
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_liftoneDoptimal_MLM_func(m=m, p=p, Xi=Xi, J=J, thetavec_matrix=bvec_bootstrap,
link = "continuation",reltol=1e-5, maxit=500, p00=rep(1/7,7), random=FALSE, nram=3)

ForLion documentation built on June 28, 2025, 1:09 a.m.