PyMC3,NUTS采样器,这是​​怎么回事?

时间:2019-09-30 00:41:12

标签: python bayesian pymc3

有人可以指出要解释我所见内容的文档吗?

Jupyter笔记本中的粉红色东西让我觉得有些问题。

使用PyMC3(顺便说一句,这是一堂课的练习,我不知道自己在做什么)。

我插入了数字,最初在对角线上出现大约0的错误,将alpha_estrate_est交换为1/alpha_est1/rate_est(并停止获取错误),但我仍然得到粉红色的东西。

此代码随练习一起提供:

# An initial guess for the gamma distribution's alpha and beta
# parameters can be made as described here: 
# https://wiki.analytica.com/index.php?title=Gamma_distribution

alpha_est = np.mean(no_insurance)**2 / np.var(no_insurance)
beta_est = np.var(no_insurance) / np.mean(no_insurance)

# PyMC3 Gamma seems to use rate = 1/beta
rate_est = 1/beta_est
# Initial parameter estimates we'll use below
alpha_est, rate_est

然后是我要添加的代码:

enter image description here

粉红色的东西会让我感到紧张还是我只是说“没有错误,继续前进”?

=======

“零问题”

---------------------------------------------------------------------------
RemoteTraceback                           Traceback (most recent call last)
RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/parallel_sampling.py", line 110, in run
    self._start_loop()
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/parallel_sampling.py", line 160, in _start_loop
    point, stats = self._compute_point()
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/parallel_sampling.py", line 191, in _compute_point
    point, stats = self._step_method.step(self._point)
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/step_methods/arraystep.py", line 247, in step
    apoint, stats = self.astep(array)
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/step_methods/hmc/base_hmc.py", line 130, in astep
    self.potential.raise_ok(self._logp_dlogp_func._ordering.vmap)
  File "/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/step_methods/hmc/quadpotential.py", line 231, in raise_ok
    raise ValueError('\n'.join(errmsg))
ValueError: Mass matrix contains zeros on the diagonal. 
The derivative of RV `alpha__log__`.ravel()[0] is zero.
"""

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
ValueError: Mass matrix contains zeros on the diagonal. 
The derivative of RV `alpha__log__`.ravel()[0] is zero.

The above exception was the direct cause of the following exception:

RuntimeError                              Traceback (most recent call last)
<ipython-input-14-36f8e5cebbe5> in <module>
     13     g = pm.Gamma('g', alpha=alpha_, beta=rate_, observed=no_insurance)
     14 
---> 15     trace = pm.sample(10000)

/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/sampling.py in sample(draws, step, init, n_init, start, trace, chain_idx, chains, cores, tune, progressbar, model, random_seed, discard_tuned_samples, compute_convergence_checks, **kwargs)
    435             _print_step_hierarchy(step)
    436             try:
--> 437                 trace = _mp_sample(**sample_args)
    438             except pickle.PickleError:
    439                 _log.warning("Could not pickle model, sampling singlethreaded.")

/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/sampling.py in _mp_sample(draws, tune, step, chains, cores, chain, random_seed, start, progressbar, trace, model, **kwargs)
    967         try:
    968             with sampler:
--> 969                 for draw in sampler:
    970                     trace = traces[draw.chain - chain]
    971                     if (trace.supports_sampler_stats

/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/parallel_sampling.py in __iter__(self)
    391 
    392         while self._active:
--> 393             draw = ProcessAdapter.recv_draw(self._active)
    394             proc, is_last, draw, tuning, stats, warns = draw
    395             if self._progress is not None:

/Local/Users/vlb/anaconda3/lib/python3.7/site-packages/pymc3/parallel_sampling.py in recv_draw(processes, timeout)
    295             else:
    296                 error = RuntimeError("Chain %s failed." % proc.chain)
--> 297             raise error from old_error
    298         elif msg[0] == "writing_done":
    299             proc._readable = True

RuntimeError: Chain 0 failed.

此处说明中的“提示”是告诉我使用1/rate_est吗?

  

您现在要创建自己的PyMC3模型!

     

对alpha使用指数优先。将此随机变量称为alpha_。
  同样,在PyMC3的Gamma中,对rate(1/1)参数使用指数优先。
  将此随机变量称为rate_(但它将作为pm.Gamma的beta参数提供)。提示:如果要建立prior的指数分布且先验估计to0的先验,请使用比例参数1 / a0。
  使用您的alpha_和rate_随机变量以及观察到的数据创建Gamma分布。
  进行10000次抽奖。


  

零问题可能是因为您正在从指数分布中采样零。

啊:

rate_est是0.00021265346963636103

rate_ci = np.percentile(trace ['rate_'],[2.5,97.5]) rate_ci = [0.00022031,0.00028109]

1 / rate_est是4702.486170152818

如果使用rate_est,我可以相信我将对零采样。

1 个答案:

答案 0 :(得分:1)

我对您的1 / alpha步骤感到怀疑。查看此讨论:https://discourse.pymc.io/t/help-with-fitting-gamma-distribution/2630

零问题可能是因为您正在从指数分布中采样零。

您可以在这里查看:https://docs.pymc.io/notebooks/PyMC3_tips_and_heuristic.html单元格[6]

我认为您对采样器的输出还可以。您可以使用traceplot检查发行版本。