I am trying to code the 2X2 matrix sigma with the 4 elements. Not sure how to code in WINBUGS. My goal is to get the posterior p's, their means and variances and create an ellipse region covered by the two posterior p's. Heres my code below:
model{
#likelihood
for(j in 1 : Nf){
p1[j, 1:2 ] ~ dmnorm(gamma[1:2], T[1:2 ,1:2])
for (i in 1:2){
logit(p[j,i]) <- p1[j,i]
Y[j,i] ~ dbin(p[j,i],n)
}
X_mu[j,1]<-p[j,1]-mean(p[,1])
X_mu[j,2]<-p[j,2]-mean(p[,2])
v1<-sd(p[,1])*sd(p[,1])
v2<-sd(p[,2])*sd(p[,2])
v12<-(inprod(X_mu[j,1],X_mu[j,2]))/(sd(p[,1])*sd(p[,2]))
sigma[1,1]<-v1
sigma[1,2]<-v12
sigma[2,1]<-v12
sigma[2,2]<-v2
sigmaInv[1:2, 1:2] <- inverse(sigma[,])
T1[j,1]<-inprod(sigmaInv[1,],X_mu[j,1])
T1[j,2]<-inprod(sigmaInv[2,],X_mu[j,2])
ell[j,1]<-inprod(X_mu[j,1],T1[j,1])
ell[j,2]<-inprod(X_mu[j,2],T1[j,2])
}
#priors
gamma[1:2] ~ dmnorm(mn[1:2],prec[1:2 ,1:2])
expit[1] <- exp(gamma[1])/(1+exp(gamma[1]))
expit[2] <- exp(gamma[2])/(1+exp(gamma[2]))
T[1:2 ,1:2] ~ dwish(R[1:2 ,1:2], 2)
sigma2[1:2, 1:2] <- inverse(T[,])
rho <- sigma2[1,2]/sqrt(sigma2[1,1]*sigma2[2,2])
}
# Data
list(Nf =20, mn=c(-0.69, -1.06), n=60,
prec = structure(.Data = c(.001, 0,
0, .001),.Dim = c(2, 2)),
R = structure(.Data = c(.001, 0,
0, .001),.Dim = c(2, 2)),
Y= structure(.Data=c(32,13,
32,12,
10,4,
28,11,
10,5,
25,10,
4,1,
16,5,
28,10,
21,7,
19,9,
18,12,
31,12,
13,3,
10,4,
18,7,
3,2,
27,5,
8,1,
8,4),.Dim = c(20, 2))