Displaying 3 results from an estimated 3 matches for "miu_i".
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min_t
2011 Apr 22
1
How to generate normal mixture random variables with given covariance function
Dear All,
Suppose Z_i, i=1,...,m are marginally identically distributed as a two normal mixture p0*N(0,1) + (1-p0) *N( miu_i, 1) where miu_i are identically distributed according to a mixture and I have generated Z_i one by one .
Now suppose these m random variables are jointly m-dimensional normal with correlation matrix M= (m_ij).
How to proceed next or how to start correctly ?
Question:
1. Are Z_i, i=1,...,m...
2012 Jul 03
2
EM algorithm to find MLE of coeff in mixed effects model
...%t(Zi)%*%solve(Sig.hat)%*%Zi%*%psi.old
Sigb=psi.old-psi.old%*%t(Zi)%*%solve(Sig.hat)%*%Zi%*%psi.old
det(Sigb)^(-0.5)
Y.minus.X.beta=t(t(y.m)-c(Xi%*%beta.old))
miu.m=t(apply(Y.minus.X.beta,MARGIN=1,function(s,B=psi.old%*%t(Zi)%*%solve(Sig.hat))
{
B%*%s
}
)) ### each row is the miu_i
tmp1=permutations(length(gausspar$nodes),2,repeats.allowed=T)
tmp2=c(tmp1)
a.mat=matrix(gausspar$nodes[tmp2],nrow=nrow(tmp1)) #a1,a1
#a1,a2
#...
#a10,a9
#a10,a10
a.mat.list=as.list(data.frame(t(a.mat)))
tmp1=permutations(length(gausspar$weights),2,repea...
2012 Jul 03
0
need help EM algorithm to find MLE of coeff in mixed effects model
...)-c(Xi%*%beta.old))
miu.m=t(apply(Y.minus.X.beta,MARGIN=1,function(s,B=psi.old%*%t(Zi)%*%solve(Sig.hat))
{
B%*%s
}
)) ### each row is the miu_i
tmp1=permutations(length(gausspar$nodes),2,repeats.allowed=T)
tmp2=c(tmp1)
a.mat=matrix(gausspar$nodes[tmp2],nrow=nrow(tmp1)) #a1,a1
#a1,a2
#......