model{
for(i in 1:n){
y[i] ~ dnorm(mu[i], tau)
mu[i] <- beta0 + beta1 * X[i,1] + beta2 * X[i,2] + beta3 * X[i,3] + beta4 * X[i,4] + beta5 * X[i,5]
}

beta0 ~ dnorm(0,0.0001)
beta1 ~ dnorm(0,0.0001)
beta2 ~ dnorm(0,0.0001)
beta3 ~ dnorm(0,0.0001)
beta4 ~ dnorm(0,0.0001)
beta5 ~ dnorm(0,0.0001)
tau ~ dgamma(0.001, 0.001)
}
