MMM.predict_posterior#
- MMM.predict_posterior(X=None, extend_idata=True, combined=True, **kwargs)#
Generate posterior predictive samples on unseen data.
- Parameters:
- Xarray_like |
array,shape(n_pred,n_features) The input data used for prediction. If scikit-learn is available, array-like, otherwise array.
- extend_idata
Boolean 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.
- **kwargs: Additional arguments to pass to sample_posterior_predictive method
- Xarray_like |
- Returns:
- y_pred
DataArray Posterior predictive samples for each input X. Shape is (n_pred, chains * draws) if combined is True, otherwise (chains, draws, n_pred).
- y_pred