BaseGammaGammaModel.sample_posterior_predictive

BaseGammaGammaModel.sample_posterior_predictive(X_pred, extend_idata=True, combined=True, **sample_posterior_predictive_kwargs)

Sample from the model’s posterior predictive distribution.

Parameters:

X_predarray, shape (n_pred, n_features)

The input data used for prediction using prior distribution..

extend_idataBoolean

Determine whether the predictions should be added to inference data object. Defaults to True.

combined: Boolean

Combine chain and draw dims into sample. Won’t work if a dim named sample already exists. Defaults to True.

**sample_posterior_predictive_kwargs: Additional arguments to pass to pymc.sample_posterior_predictive

Returns:

posterior_predictive_samplesDataArray, shape (n_pred, samples)

Posterior predictive samples for each input X_pred