"flt.var" <- function(fpar, x,width, mix.terms,z=NULL,zdim=0,pt=FALSE)
# flt.var - computes hessian for v-c matrix (see pg 62 of Buckland et al 2002)
# Value: variance-covariance matrix of parameters
# Functions Used: flt
{
#
fpar1<-fpar
parmat=NULL
eps<-0.0001
# Compute first partial (numerically) of log(f(y)) for each observation
# for each parameter and store in parmat (n by length(fpar))
for (i in 1:length(fpar)){
fpar[i] <- fpar1[i]-eps*fpar1[i]
x1=log(rowSums(eval.pdf(fpar,x,width,mix.terms,0,"hn",z,zdim,pt)))
fpar[i] <- fpar1[i]+eps*fpar1[i]
x2=log(rowSums(eval.pdf(fpar,x,width,mix.terms,0,"hn",z,zdim,pt)))
parmat=cbind(parmat,(x2-x1)/(2*eps*fpar1[i]))
}
#
# Compute varmat using first partial approach (pg 62 of Buckland et al 2002)
#
varmat=matrix(0,ncol=length(fpar1),nrow=length(fpar1))
for(i in 1:length(fpar1))
for(j in 1:length(fpar1))
varmat[i,j]=sum(parmat[,i]*parmat[,j])
return(varmat)
}
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