I don’t know if this is the right place to ask or not, but I am curious to know what is happening if I pass the following model for sampling in Numpyro. I mean what is the posterior, prior, likelihood over here:
def ll(c, J, tau, mu, theta):
return dist.Normal(jnp.full(J,mu), jnp.exp(tau*c)).log_prob(theta) - dist.Normal(jnp.full(J,mu), jnp.exp(tau)).log_prob(theta)
def sample_modell(J, c):
mu = numpyro.sample('mu', dist.Normal(0, 1))
tau = numpyro.sample('tau', dist.Normal(0,1))
theta = numpyro.sample('theta', dist.Normal(jnp.full(J,mu), jnp.exp(tau)))
numpyro.factor('theta_ll', ll(c, J, tau, mu, theta))