BaseDelayedSaturatedMMM.sample_prior_predictive

BaseDelayedSaturatedMMM.sample_prior_predictive(X_pred, y_pred=None, samples=None, extend_idata=False, combined=True, **kwargs)

Sample from the model’s prior predictive distribution.

Parameters:

• X_pred (array, shape (n_pred, n_features)) – The input data used for prediction using prior distribution.

• samples (int) – Number of samples from the prior parameter distributions to generate. If not set, uses sampler_config[‘draws’] if that is available, otherwise defaults to 500.

• extend_idata (Boolean determining whether the predictions should be added to inference data object.) – Defaults to False.

• 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_prior_predictive)

Returns:

prior_predictive_samples – Prior predictive samples for each input X_pred

Return type:

DataArray, shape (n_pred, samples)