def get_global_entropy(glmm_par):
info_mu = glmm_par['mu']['info'].get()
info_beta = glmm_par['beta']['info'].get()
tau_shape = glmm_par['tau']['shape'].get()
tau_rate = glmm_par['tau']['rate'].get()
return \
ef.univariate_normal_entropy(info_mu) + \
ef.univariate_normal_entropy(info_beta) + \
ef.gamma_entropy(tau_shape, tau_rate)
def test_gamma_entropy(self):
shape = 3.0
rate = 2.4
gamma_dist = sp.stats.gamma(a=shape, scale=1 / rate)
self.assertAlmostEqual(gamma_dist.entropy(),
ef.gamma_entropy(shape, rate))
def entropy(self):
return ef.gamma_entropy(
shape=self['shape'].get(), rate=self['rate'].get())