BaseMMM.predict_posterior

BaseMMM.predict_posterior(X_pred, extend_idata=True, combined=True, **kwargs)

Generate posterior predictive samples on unseen data.

Parameters:

X_predarray_like if sklearn is available, otherwise array, shape (n_pred, n_features)

The input data used for prediction.

extend_idataBoolean 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 sample_posterior_predictive method

Returns:

y_predDataArray, shape (n_pred, chains * draws) if combined is True, otherwise (chains, draws, n_pred)

Posterior predictive samples for each input X_pred