model{
   for(i in 1:N1){
      K[i,1:2]~dmnorm(mu,precI)
   }
   precI<-inverse(prec)
   prec[1,1]<-sigma[1]^2
   prec[2,2]<-sigma[2]^2
   prec[1,2]<-rho*sigma[1]*sigma[2]
   prec[2,1]<-rho*sigma[1]*sigma[2]
   # Priors
   for(j in 1:N2){
      mu[j]~dnorm(0,0.0001)
      lambda[j]~dgamma(0.001,0.001)
      sigma[j]<-pow(lambda[j],-0.5)
   }
   rho~dunif(-1,1)
}