使用pm.fast\u sample\u posterior\u预测的Pymc3形状误差

2024-06-16 14:50:39 发布

您现在位置:Python中文网/ 问答频道 /正文

我使用PYMC3拟合了一个双组分混合模型,并希望从后验模型中取样

我可以使用pm.sample\u posterior\u predictive()很好地执行此操作,但是当我尝试使用pm.fast\u sample\u posterior\u predictive()执行此操作时,我收到以下值错误:

ValueError: input operand has more dimensions than allowed by the axis remapping

我不确定这是为什么,也无法在PYMC3文档中找到原因

代码如下:

with pm.Model() as model:
    alpha_mu = 1.0 / y.mean()
    lam1 = pm.Exponential('lam1', lam=1)
    lam2 = pm.Exponential('lam2', lam=2)

    pois1 = pm.Poisson.dist(mu=lam1)
    pois2 = pm.Poisson.dist(mu=lam2)

    w = pm.Dirichlet('w', a=np.array([1, 1]))

    mix = pm.Mixture('mix', w=w, comp_dists = [pois1, pois2], observed=y)
    # optimization
    mean_field = pm.fit(n=10000, obj_optimizer=pm.adagrad(learning_rate=0.1))
    trace = mean_field.sample(1000)
    # plot trace
    pm.traceplot(trace,varnames=['lam1','lam2','w'])
    plt.show()
    # plot Preditive Posterior Check
    ppc = pm.fast_sample_posterior_predictive(trace, samples=len(y))

感谢您的帮助


Tags: sample模型tracemeanfastpredictivepymc3mu