#' Simulate Z based on a probit model
#'
#' Simulates a random latent matrix Z given its expectation, dyadic correlation
#' and a binary relational matrix Y
#'
#'
#' @usage rZ_bin_fc(Z, EZ, rho, Y)
#' @param Z a square matrix, the current value of Z
#' @param EZ expected value of Z
#' @param rho dyadic correlation
#' @param Y square binary relational matrix
#' @return a square matrix , the new value of Z
#' @author Peter Hoff
#' @export rZ_bin_fc
rZ_bin_fc <-
function(Z,EZ,rho,Y)
{
# simulates Z under the contraints
# (1) Y[i,j]=1 => Z[i,j]>0
# (2) Y[i,j]=0 => Z[i,j]<0
sz<-sqrt(1-rho^2)
ut<-upper.tri(EZ)
lt<-lower.tri(EZ)
Y[is.na(Y)]<- -1
for(y in c((-1):1))
{
lb<-c(-Inf,-Inf,0)[y+2] ; ub<-c(Inf,0,Inf)[y+2]
for(tri in 1:2)
{
if(tri==1){ up<-ut & Y==y }
if(tri==2){ up<-lt & Y==y }
ez<- EZ[up] + rho*( t(Z)[up] - t(EZ)[up] )
zup<-ez+sz*qnorm(runif(sum(up),pnorm((lb-ez)/sz),pnorm((ub-ez)/sz)))
zerr<-which(abs(zup)==Inf)
if(length(zerr)>0){ zup[zerr]<-(Z[up])[zerr] }
Z[up]<-zup
}
}
##
c<-(sqrt(1+rho) + sqrt(1-rho))/2
d<-(sqrt(1+rho) - sqrt(1-rho))/2
E<-matrix(rnorm(nrow(Y)^2),nrow(Y),nrow(Y))
ZP<-EZ + c*E + d*t(E)
A<-( (Y== -1) | ( sign(ZP) == sign(Y-.5)) ) ; diag(A)<-TRUE
A<-A & t(A)
Z[A]<-ZP[A]
##
## this line now redundant because of previous chunk
diag(Z)<-rnorm(nrow(Z),diag(EZ),sqrt(1+rho))
##
Z
}
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