BaseDelayedSaturatedMMM.sample_posterior_predictive#
- BaseDelayedSaturatedMMM.sample_posterior_predictive(X_pred, extend_idata=True, combined=True, **kwargs)#
Sample from the model’s posterior predictive distribution.
- Parameters:
X_pred (array, shape (n_pred, n_features)) – The input data used for prediction using prior distribution..
extend_idata (Boolean determining whether the predictions should be added to inference data object.) – Defaults to True.
combined (Combine chain and draw dims into sample. Won't work if a dim named sample already exists.) – Defaults to True.
**kwargs (Additional arguments to pass to pymc.sample_posterior_predictive)
- Returns:
posterior_predictive_samples – Posterior predictive samples for each input X_pred
- Return type:
DataArray, shape (n_pred, samples)