model{ # likelihood for(i in 1:N){ X1[i] ~ dnorm(muA,sig) X2[i] ~ dnorm(muB,sig) } # prior muA ~ dunif(-100,100) muB ~ dunif(-100,100) sig <- pow(sigma,-2) sigma ~ dt(0,1,1)T(0,) }