小编iva*_*ero的帖子

我正在通过书本学习贝叶斯推理Bayesian Analysis with Python。但是，在使用时plot_ppc，我收到AttributeError了警告

/usr/local/Caskroom/miniconda/base/envs/kaggle/lib/python3.9/site-packages/pymc3/sampling.py:1689：UserWarning：样本参数小于 nchains 乘以 ndraws，一些绘制和/或链可能不会在返回的后验预测样本中表示\nwarnings.warn(

模型是

shift = pd.read_csv(\'../data/chemical_shifts.csv\')\n\nwith pm.Model() as model_g:\n    \xce\xbc = pm.Uniform(\'\xce\xbc\', lower=40, upper=70)\n    \xcf\x83 = pm.HalfNormal(\'\xcf\x83\', sd=10)\n    y = pm.Normal(\'y\', mu=\xce\xbc, sd=\xcf\x83, observed=shift)\n    trace_g = pm.sample(1000, return_inferencedata=True)\n

如果我使用以下代码

with model_g:\n    y_pred_g = pm.sample_posterior_predictive(trace_g, 100, random_seed=123)\n    data_ppc = az.from_pymc3(trace_g.posterior, posterior_predictive=y_pred_g) # \'Dataset\' object has no attribute \'report\'\n

我得到“数据集”对象没有属性“报告”。

如果我使用以下代码

with model_g:\n    y_pred_g = pm.sample_posterior_predictive(trace_g, 100, random_seed=123)\n    data_ppc = az.from_pymc3(trace_g, posterior_predictive=y_pred_g) …