Function sample_from_prior

bayesian_ml/4/npbgmm.py:54–58

(c0, m0, a0, B0)

def sample_from_prior(c0, m0, a0, B0):
  precision0 = wishart.rvs(df=a0, scale=np.linalg.inv(B0))
  cov = np.linalg.inv(precision0)
  mean = mvn.rvs(mean=m0, cov=cov/c0)
  return mean, cov


# samples mu, sigma from P(mu, sigma | X)