小编Jav*_* C.的帖子

要学习PyMC,我正在尝试做一个简单的隐马尔可夫模型,如下所示:

with pymc3.Model() as hmm:
    # Transition "matrix"
    a_t = np.ones(num_states)
    T = [pymc3.Dirichlet('T{0}'.format(i), a = a_t,  shape = num_states) for i in xrange(num_states)]
    # Emission "matrix"
    a_e = np.ones(num_emissions)
    E = [pymc3.Dirichlet('E{0}'.format(i), a = a_e,  shape = num_emissions) for i in xrange(num_states)]
    # State models
    p0 = np.ones(num_states) / num_states
    # No shape, so each state is a scalar tensor
    states = [pymc3.Categorical('s0', p = p0)]
    emissions = [pymc3.Categorical('z0',
                               p = ifelse(eq(states[0], 0), E[0], ifelse(eq(states[0], 1), E[1], E[2])),
                               observed …