model { for (i in 1:n) { x[i] ~ dnorm(mu,tau) # Likelihood function for each data point } mu ~ dnorm(0,0.0001) # Prior for mu tau <- 1 # Prior for tau, actually a fixed value sigma <- 1/sqrt(tau) # Prior for sigma (as a function of tau) } # Data list(x=c(-1.10635822, 0.56352639, -1.62101846, 0.06205707, 0.50183464, 0.45905694, -1.00045360, -0.58795638, 1.01602187, -0.26987089, 0.18354493 , 1.64605637, -0.96384666, 0.53842310, -1.11685831, 0.75908479 , 1.10442473 , -1.71124673, -0.42677894 , 0.68031412), n=20) # Results | node | mean | sd | MC error | 2.5% | median | 97.5% | start | sample | | mu | -0.06355 | 0.2235 | 0.002986 | -0.5034 | -0.06203 | 0.3738 | 1001 | 5000 |